of 10th EWGT Meeting
and 16th Mini-EURO Conference
Poznan, 13-16 September, 2005
Mission, activities and expectations of the EURO Working Group on Transportation
In this presentation the EURO Association is outlined with its goals and instruments. Then, the Operations Research and Transportation Systems methodologies are recalled with the indication of some trends in the development of innovative methods able to deal with more complex problems and new topics. Moreover, the profile of the EURO Working Group on Transportation is presented with possible improvements in the organisation and activities.
Evaluation functions for real world problems: a case study
This paper contains a general discussion on the prediction and optimization issues present in dynamic environments, and explains the concept of Adaptive Business Intelligence. The paper also presents a real world case study on a car distribution system. The problem is set in a dynamic environment and requires (1) prediction of prices for cars sold at auction sites, (2) optimization of car distribution, and (3) frequent adaptation of the prediction model.
Overview of road and motorway traffic control strategies
Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput which can be countered via suitable control measures and strategies. A concise overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks and route guidance. The paper concludes with a brief discussion of future needs in this important technical area.
Bee colony optimization – a cooperative learning approach to complex transportation problems
Various natural systems teach us that very simple individual organisms can create systems able to perform highly complex tasks by dynamically interacting with each other. The Bee Colony Optimization Metaheuristic (BCO) is proposed in this paper. The artificial bee colony behaves partially alike, and partially differently from bee colonies in nature. The BCO is capable to solve deterministic combinatorial problems, as well as combinatorial problems characterized by uncertainty. The development of the new heuristic algorithm for the Ride-matching problem using the proposed approach serves as an illustrative example and shows the characteristics of the proposed concepts.
A multiobjective oriented network design model for on ground aircraft's routing management
In this paper a network design model is presented for the problem of how to define an optimal airport topology in order to attend the conflicting movements of the aircrafts on ground during short to medium planning periods and taking into account the dynamic aspects of their interfering movements. Given a set of decision variables affecting the airport's topology, the model balances a set of conflicting objectives or factors and their results are compared with the routing decisions taken from real data. The model is primarily solved using "B&B" and the multicriteria approach presented is investigated using real test networks.
Applying genetic techniques to the tactical flight level assignment
Due to technical and economic reasons, commercial flights usually concentrate on very few cruising flight levels, thus implying high conflict or collision risk. Here, we aim at distributing the aircraft among the flight levels to minimize a global conflict risk indicator, while limiting the overall fuel overconsumption induced by assigning aircraft to flight levels different from their chosen ones. The method presented involves a population based genetic algorithm, especially designed for our problem. This paper mainly discusses the principle of this method as well as its first results.
Pricing and scheduling strategies for air cargo carriers: a non-cooperative game approach
As an oligopoly market, the pricing and service strategies of one air cargo carrier would affect and be affected by the strategies adopted by others. First, we formulated the cargo demand as a Logit function to revealed forwarders’ preferences toward freightage, flight frequency and service reliability. Next, we calibrated the model by using SP and RP survey data. Then by applying one of the non-cooperative game approaches, i.e., Bertrand model, we solved the optimal freightage and flight schedules of air cargo carriers under variable O-D demands.
Simulation model for the mission profiles and energy consumption of a transit mode
The objective of the paper consists in the development of a valid procedure able to plan the addition of Zero Emission Vehicles (ZEV) to existing lines. This led to the elaboration of the 3 analytical models that evaluate mission profiles (speed vs space and time), energy consumption and battery autonomy of an electric urban transit mode/vehicle. The models are determined on the basis of the characteristics of the line, of the various service condition and of the technical and performance characteristics of the vehicle considered. The mission profile model allows to discriminate between the various types of diagrams, triangular or trapezoidal, according to the values assumed by a parameter called "profile ratio" and the running speed that exclusively considers stops due to traffic.
Traffic parameters estimation to predict road side pollutant concentrations using neural networks
The analysis aims to evaluate which among traffic parameters (flows, queues length, occupancy degree and travel time) are most important in order to forecast CO and C6H6 concentrations. The study area was identified by Notarbartolo Road and bounded by Libertà Street and Sciuti Street in the urban area of Palermo. In this area, various loop detectors and one pollution monitoring site were located. Traffic data were estimated by SUMO micro-simulator software. Traffic and weather data were used as input variables to predict pollutant concentrations by using neural networks.
Monitoring and assessment of daily exposure of residential population to highway traffic noise in Jalgaon urban center
Heavy traffic is a major source of noise pollution in the urban centers. Higher noise levels are observed in the residential area near highway passing through Jalgaon city. The exposure of population to the higher noise levels affects on the hearing capability. In the present study hearing impairment was observed in the population exposed to higher noise levels.
Impact of highway traffic pollution on lung function of residential population in Jalgaon urban center
Higher levels of pollutants are observed in the residential area near the highway passing through Jalgaon urban center. The continuous exposure of the population to these higher levels of air pollutants leads in decrease in the lung capacity. Decline in the lung parameters FVC, FEV1, and PEFR are observed in the population residing in the area than the non-exposed population.
Second order traffic flow modeling: supply-demand analysis of the inhomogeneous Riemann problem and of boundary conditions
Recently Aw, Rascle and Zhang introduced a second order model (ARZ) that does nor exhibit the usual drawbacks of this family of models, i.e. negative velocities and/or densities. In this paper we analyze the inhomogeous Riemann problem for this model, which is shown to be equivalent to the inhomogeous Riemann problem for a related first order model with modified equilibrium flow density relationship. The boundary conditions for the ARZ model are deduced. They can be expressed in terms of an upstream demand and downstream supply.
Second order traffic flow modelling: the Riemann problem resolution in homogeneous case without relaxation term
This paper presents the theoretical discussions, the improvement and the complete resolution, in the homogenous case, of the recent second order macroscopic model developments suggested by Aw & Rascle and Zhang respectively. The improved model respects strictly the anisotropic character and solve the lacks concerning the resolution of Riemann’s problem.
The link transmission model: an efficient implementation of the kinematic wave theory in traffic networks
This paper describes a numerical solution method for a dynamic network loading model that is consistent with the first order kinematic wave theory. The proposed procedure, called link transmission model (LTM), only requires calculations at network nodes. Compared to the cell transmission model (CTM), the computational complexity of the LTM is about n times smaller for the same level of accuracy, where n is the mean amount of cells in a homogeneous network link.
A model for the analysis of regional accessibility for freight transportation
Accessibility models are very important to evaluate transportation systems. Even though, there are a lot of researches on this matter, there are many aspects that remain unexplored. Most of the accessibility indicators are related to urban transportation systems and not concerned to freight transport in a regional context. By a literature review it was identified some accessibility models used in several studies and the principal variables that compose them. Thus, starting from this analysis, considering the freight transport characteristics, a model to evaluate the accessibility in the context of regional freight transport is proposed.
A sustainable urban freight transport system
In this work, we propose a system for urban freight transport managed by an insertion algorithm for the pickup and delivery problem and characterized by a fleet of electrical vehicles. To improve the use of such a system, a toll for the most polluting vehicles is introduced, with the aim of reducing emissions and allowing the establishment of scale economies. In order to determine the influence of the pricing policy on the mode choice between the sustainable and the traditional system, an equilibrium model will be introduced. An application of the proposed model to the network of Rome is also presented.
Vehicle replacement planning in freight transportation companies
The paper presents the method that allows defining the optimal replacement policy for vehicles utilized in a freight transportation company. The mathematical model of the problem as well as the solution procedure are described. The problem has been formulated in terms of the singlecriterion, linear, deterministic, static and discrete mathematical programming. The exact solution procedure has been proposed. The problem has been solved as a real life case study.
Trends in modelling supply chain and logistic networks
According to the new tendencies in marketplace, such as the growth and spread of e-commerce and e-business, Supply chains and Logistics are naturally being modeled as distributed systems. Companies are organized as Demand and Supply network and the global logistics system is performed by a large-scale world-wide network of local service enterprises. Referring to such scenario, multi-agents and operations research approaches in modelling classical and new complex problems are reviewed and illustrated. Operation Research techniques for centralized optimization are discussed with reference to classical resource allocation and workflow problems.
Comparing transport contracts in a multi-period setting
The optimal contract and contract parameters are presented when a shipper and a capacitated transport service provider interact repeatedly to renew procurement agreements for one product in a multi period game. Three forms of contracts which enable credible information sharing are analyzed: a price-only relational contract, a minimum purchase commitment or a quantity flexibility contract. A back-stop spot market for transport capacity is available to the buyer. Both transport spot price and received demand are dependent exogenous stochastic processes. Conditions for equilibria which do not depend upon any assumption of relative bargaining power between players are presented. If buyer and seller are offered the choice of transactional form, Nash equilibria require tighter conditions on contracts and parameters than previously envisaged in the literature. This paper meshes together different research strands: supply chain multi period game as well as recent supply chain contracts. Problems, which up till now were considered in isolation, are represented in one setting.
Logistics terminals planning for an optimal freight mobility system: an application on a regional scale
This paper suggests an approach to plan logistics terminals. In particular, it describes an application to the freight transport by road involving the sicilian area. The modelling framework, which is inspired by the “Stackelberg game” paradigm, uses an objective function representing some relevant public interests and simulates the choice behaviour of freight transport operators. Basic assumptions concern the involvement of the public sector in terms of a share in investments and incentives to foster the use of terminals; for some scenarios on the public budget constraints, a set of optimal location patterns is determined.
"Are we moving in the right direction?" Transport's environmental impact assessment with Electre III
"Are we moving in the right direction?" is TERM’s key question on the environmental performance of transport in Europe. Here, we apply ELECTRE III to answer this question, that has been left open ever since. Indicator weights are transferred from Life Cycle Assessment methodology and proposed for discussion. Judging from the indicators provided, the environmental performance from the road vehicles in EU15 may become better if transport’s increasing land take and fragmentation can be halted. Otherwise, improvements do not seem enough to balance the increasing energy consumption and carbon dioxide emissions.
Sustainable mobility evaluation in urban areas
This work applies the sustainable evaluation to the case of transport and land use planning in urban areas. A set of indicators according the three dimensions of sustainability, environment, economics, and social aspects, are defined to evaluate the mobility in urban areas. The aim of this work is to present a procedure to define a Sustainable Mobility Index in Urban Areas. A set of transports and land use indicators was proposed and used in a Multicriteria Analysis to define the Index. Based on the Multicriteria Analysis the indicators priority was defined by a group of specialists in urban and transport planning.
A bilevel programming model to optimising the modal distribution of charge in urban environments with congestion: the case of the new port of Laredo
In this paper a bilevel programming model is presented for the resolution of the modal distribution in the charge provisioning of construction works in urban environments. The model is applied to the construction of the new port of Laredo where the modal distribution is optimized between trucks and barges, for commodity type and period.
The comparison of multiobjective ranking methods applied to solve the mass transit systems' decision problems
The paper presents the application of the Multiple Criteria Decision Aiding (MCDA) methodology for the decision problems arising in mass transit systems (MTS-s). Three categories of problems are considered, i.e. : evaluation of the MTS development scenarios, ranking of the maintenance work contractors for the MTS renovation project, selection of the transportation mode for the MTS. All of them are formulated in terms of multiobjective ranking problems and solved by the following MCDA methods: Electre, Oreste, Mappac, AHP and UTA. The comprehensive comparison of the methods is carried out and their suitability for solving the MTS decision problems is discussed.
A gravitational approach for locating new services in urban areas
In this work we face the problem of locating new services in urban areas. Given a digraph whose nodes represent urban zones and arcs are the flow connections between them, we have to decide in which node new service centers can be optimally located on the basis on the evaluation of the efficiency of other centers that have been previously located in different nodes. We first derive the main parameters that could influence this locative choice and present a model originating from the classical gravitational and attractivity approach used in the competitive location problem. This well known model is here originally applied in the presented case study related to the city of Genoa, Italy, where we had the need of evaluating different locations for opening food and rest service centers.
A multimodal approach for managing transportation design problems of real size networks
Most network design models proposed in the literature analyse only one transportation mode (road or transit systems) and are based on the assumption of rigid modal split. To overcome these limits, the authors propose models and algorithms for solving transportation design problems from a multimodal point of view. The paper also provides two applications of the multimodal approach in the case of fare design.
A model of cost optimization for the location of bus-stop
This work provides a model for the location of bus-stops in urban public transport, which is based on the optimization of a cost function of the transport system. The cost function includes the user costs, the operating costs and the costs of constructing the bus-stops. In order to obtain the solution to the problem posed, we estimates the optimal number of stops and locates them in accordance with the configuration of the network, the transport demand and the traffic existing in the various stretches which compose the lines. Besides providing the location of bus-stops, this model also allows us to size the service by calculating the frequency and number of buses which satisfy the demand.
A rapid transit network design model in regard to transfers
In this paper we propose a model for the problem of designing a rapid transit network which includes transfers. Our objective is to maximize the number of expected users in the transit network taking limited budgets into consideration. Additionally, the existing competition between private and public modes is assumed when the generalized cost for the user trips is calculated. Some computational experiment with the model is provided.
Urban rapid transit network capacity expansion
The rapid transit network design problem consists on the location of the train alignments and stations in an urban traffic context. The location problem incorporates the demand decisions about the mode and route that they choose to realize the urban trips. The capacity expansion incorporates to the location problem some relevant criteria about the cost of the investment and the future utilization of the infrastructure. Some basic methodology to be used in this context is considered.
Improvement of OD estimation based on disaggregated flow information
In this paper the redundant information issue of OD estimation models, based on information minimization (IM) and entropy maximization (EM) theories, is briefly reviewed and examined. A systematic approach is proposed to eliminate the redundant information from the flow data at intersection level. The result shows that with the proposed elimination method, the IM model provides more accurate OD estimates than the EM model, not only when the available information for the route choice proportions is by 100% correct, but also when these calculated proportions are not precise.
Bridging the gap between transport engineering and economic research
The case of linking origin-destination tables of JICA-DOTC survey and interregional flows in SAM in the Philippines.
Dynamic travel demand estimation using real-time traffic data
The objective of this paper is on the development of a dynamic travel demand estimation model using real-time traffic data collected from Freeway Traffic Management System (FTMS). In the existing studies, the micro-simulation models had been used to get a path-link distribution proportion. These lead to use a bi-level approach between a traffic flow model and a travel demand estimation model. However, the approach is likely to produce biased estimation due to some discrepancies between dynamic demand and traffic flow models. The paper proposes a novel method based on a genetic algorithm, which is able to remove the bi-level approach. The proposed methodology is evaluated by using the real-time data of SOHAEAN freeway in Seoul, South Korea.
A heuristic for the estimation of time-dependent origin–destination matrices from traffic counts
We consider the problem to estimate time-dependent origin–destination matrices from traffic counts. We propose an iterative algorithm, based on difference quotients, for expressing how the link flows are changed with respect to a change of the travel demand. The method is an extension to previously proposed methods for the time-independent case. It has been implemented together with the mesoscopic traffic assignment software Mezzo and tested for a network modeling the city of Stockholm.
Marginal value of wireless internet connection on trains: implications for mode-choice models
Attribute-specific mode choice models predict the distribution of traffic among the various modes available, on the basis of some attributes. We consider the effect on valuation of one important attribute of mode choice, namely the travel time, for a population of commuters, when wireless internet access (wi-fi) is provided on trains. We use activity demand models to derive certain parameters of mode-choice models. From these parameters, the effect of changes in the use, and hence the valuation, of travel time caused by the presence of internet access, may be determined. The proposed model can be used to estimate willingness to pay for these services on commuter trains. It may also be used to estimate the effect of the provision of wi-fi on rail market share.
Determining lack of information about public transit system
The most preferred method for solving urban traffic problems is supporting the public transit systems. For this reason, enough information about the system should be offered to potential users. Lack of information about public transit system causes delays, dissatisfaction and passing to other transportation modes. In this study, two public surveys were made among public bus system users at city center bus stops in city of Eskisehir, TURKEY to learn their information level and general satisfaction about the bus system.
Public transport network design and appraisal -- a case study of Porto
The city of Porto is currently building an extensive light rail network. In order to reduce costs and improve integration with the new mode, the local bus company is completely re-designing its network. This paper presents an evaluation of different public transport networks, from the point of view of accessibility and efficiency. Our results clearly show that it is possible to improve global accessibility across the system while reducing resource requirements. This is achieved partly by improving bus services to LRT stations and by improving service frequency on the main corridors not served by the LRT.
Design of operations of personal rapid transit systems
Personal Rapid Transit is a system of automated taxis travelling on their own guideway. Trips are non-stop to destination as stations are off-line. Vehicles are available on-demand rather than on fixed schedules. To date the system is still in the research stage. Performance parameters that are key to the design of operations are passenger waiting time at stations and the occurrence of wave-off events when a full station prevents an occupied vehicle from entering. The paper provides a methodology for the design of operations and discusses the sensitivity of the main performance parameters to transport demand.
Simulation and evaluation of integrated public transport
Integrated public transportation service is a new interesting form of service combining a fixed route service with a demand responsive service. The aim of this work is to find guidelines to help operators of public transport to design this service. It is then important to analyse and evaluate how the attractiveness and operating costs for the service depend on the type of demand responsive service used, and on design parameters related to the fleet of vehicles, the structure of the transportation network and the personal service commitments made to the passengers. The evaluation is made using simulation and the LITRES-2 public transport modelling system. Computational results are presented.
Trip time prediction in mass transit companies. A machine learning approach
In this paper we discuss how trip time prediction can be useful for operational optimization in mass transit companies and which machine learning techniques can be used to improve results. Firstly, we analyze which departments need trip time prediction and when. Secondly, we review related work and thirdly we present the analysis of trip time over a particular path. We proceed by presenting experimental results conducted on real data with the forecasting techniques we found most adequate, and conclude by discussing guidelines for future work.
A GIS approach to evaluate bus stop accessibility
This paper proposes a methodology to assess public transportation access in urban area by using a geographical information system based on pedestrian network with presence of the obstacles. This methodology allows to plan the "optimal location" of the new bus stops or to modify their location so as to serve most of users in the urban area. Its goal is to get ready a support system for planners, policy makers, transport operators and disability organizations to evaluate the access to public transport system in urban areas
Generating dense railway schedules
In order to cope with increasing train frequencies, a method for creating dense schedules in station regions is necessary. We propose a two level method in which dense tentative timetables are obtained applying Simulated Annealing on an aggregated track topology modelled with Petri Nets. These timetables are then checked for feasibility in detailed local track topologies. Results show that timetables conforming to operational demands are found within a few minutes.
The effectiveness of static implications in real-time railway traffic management
We study a real-time railway traffic management problem. It consists in adjusting train timetables in order to restore feasibility when unforeseen events in the network make unfeasible the off-line generated timetable. The problem can be formulated as a huge job-shop problem with blocking constraints, which has to be solved within strict time limits due to real-time constraints. Unfortunately, even finding a feasible solution is an NP-complete problem. To this aim, implication rules are a powerful tool to design fast and effective solution algorithms. In this paper we present a new simple static implication rule for the blocking job-shop problem, and its application to the real-time railway traffic management problem.
A computational experience, based on a real railway infrastructure, shows the effectiveness of the implication rule to speed up a heuristic solution algorithm.
Joint pricing and network capacity setting problem
We consider the problem of jointly determining installed capacity levels and associated tariffs on the arcs of a multicommodity transportation network. We model this situation as a joint pricing and network capacity setting problem. Capacities are available at discrete, non uniform levels. This problem is first formulated as a mixed integer bilevel program. Next, we develop an algorithmic framework and give numerical results showing that our procedure is capable of solving problems of significant sizes.
Integrated transport and land use policies for developing countries: relocation of residences, road pricing and transit subsidy
Incompatibilities between urban transport and land use are rapidly growing in developing countries. Due to this mismatch, vehicle ownership is increasing dreadfully causing urban areas for various problems including congestion and air pollution. This study attempts to investigate the household travel behaviour on vehicle ownership, mode choice and trip sharing aspects by developing a nested logit (NL) model as a basic step of the analysis. Then, the estimated NL model is used for integrated policy assessments based on relocation of residences, road pricing, and reduction of transit fares. The policy impacts are presented as the reductions of vehicle kilometres of travel and air pollution considering Bangkok Metropolitan Region as a case study.
Macroeconomic analysis of transport pricing regimes for the EU
This paper presents a macroeconomic analysis of 10 different transport pricing policies that have been designed in EU funded projects like REVENUE or TIPMAC. The policies differ in terms of where and for which mode charges are introduced and how revenues of the charges are allocated to the economic actors. The impact analysis is performed by using the integrated economy – transport – environment assessment model ASTRA. The analysis identifies a set of transport-economic mechanisms that are relevant to consider and to design successful pricing policies for transport.
Combining vehicle routing models and microscopic traffic simulation to model and evaluating city logistics applications
The distribution of goods based on road services in urban areas contribute to traffic congestion, and generates environmental impacts As a consequence the design and evaluation of City Logistics applications requires an integrated modeling framework in which all components could work together. including also the dynamic aspects of the underlying road network, namely if ICT applications are taken into account. This paper presents a methodological proposal based on an integration of vehicle routing and, dynamic traffic simulation models that emulate the actual traffic conditions to determine the optimal dynamic routing and scheduling of the vehicle, that has been developed and tested in the European Project MEROPE of the INTERREG IIIB Programme, and in the national project SADERYL, sponsored by the Spanish DGCYT based on the microscopic traffic simulator AIMSUN.
A study on calibration of generated route choice set for railway passengers
Railway passengers in the Tokyo Metropolitan Area (TMA) have had several alternative railway routes from their origins to destinations, since the TMA boasts one of the most extensive urban railway networks in the world. Yet, improvement of various kinds of service facilities has been constantly called for to enhance the level of services for railway passengers. In this case, the route choice behavior of the passengers should be carefully analyzed with suitable choice sets which, however, lack a standard procedure. The paper tries to answer the question of how to find procedures of creating the set and how to calibrate the generated set. For this purpose, a special survey of offices in the CBD, where the passengers commute from a wider TMA area, is undertaken.
A reinforcement learning model for simulating route choice behaviours in transport network
This paper proposes a new algorithm for finding disaggregate user equilibrium on a congested network, in which a driver is assumed to be an agent who learns from driving experiences to get maximal payoffs under the condition of incomplete travel information. Day-to-day route choice behaviours of each driver are formulated as a kind of repeated game with learning, and a simple adoptive procedure that lead to Nash equilibrium is proposed. The model presented here can cover a wide range of network equilibrium concepts from deterministic to stochastic user equilibriums.
Finding dissimilar efficient routes for hazmat shipments
We study the problem of finding hazmat road transportation paths minimizing both the total risk of hazmat shipments and the total transportation cost, meanwhile guaranteeing a certain level of risk equity over the population. To ensure the selection of a set of paths that also guarantee an equitable spread of the risk over the population, we introduce a new similarity index. The problem is mathematically formulated and is heuristically solved, and the proposed model and algorithm are evaluated on realistic problem instances.
Analysis about quality in the freight transportation and direct effect in the management of a transportation organization
Traditionally, the logistic world has not been identified like pioneer or innovating about total quality. Is not simple to find a diversity of Programs of Quality in the companies of the sectors related to this and, of course, to identify "Good Practices" that was widely recognized in this difficult business. If we paid attention to the industrial and services world, and observe the advances of both in the application of the concepts of management Excellence, we will find logistic element like one of the critical factors of the effectiveness and efficiency of many of its main processes. The services world is "just in time": the service delivery simultaneously that takes place, so the necessity to obtain logistic services of high quality exists. If we want to state that this quality really exists, we must show it in other parameters, those that are excellent for the customer and own company. Logistics is a sector that has experienced a great growth in the last years. Logistics is the main tool to get a place in this competitive world. The challenge of transport is to grow, improving the quality and the downtimes to the customers. The transport centers and the freight terminals in ports and airports become logistic platforms that allow the perfect combination of transport modes. The transport performance is intimately bound up with the logistics. In logistics, the quality must be offered without it was demanded, because all methods of transport must contain it, besides a suitable management and control of that quality.
Tracking waves for modelling the impact of incidents
In order to model the impact of incidents an alternative resolution method is proposed for the Lightill-Whitham-Richards model. It is based on an explicit handling of shock waves (generation, tracking and collision). Contrary to finite difference methods which impose a fixed discretization grid, the Wave Tracking method is event based. The different possible events are studied and they lead to the resolution of Riemann problems or extended Riemann problems which are proved to generate waves.
Space allocation and location matching in container terminals
Operational efficiency at container terminals has become very important as the amount of traffic going through such terminals has increased a lot in the last two decades. In this study, the problem of determining the locations to place the containers and matching inbound and outbound containers for efficiency of internal trucks are considered. The problem is decomposed, approximately, into two tractable problems and experimental results are reported.
A Petri net model for simulation of container terminals operations
In this paper a model to simulate the operation at a container terminal is proposed. In our model the terminal is assumed as a system that has to be designed and/or controlled in order to achieve the best performance on the basis of the existing resources. The terminal itself is assumed to be a node of the existing freight intermodal network that could improve his reliability from improving the performance of the activities at the nodes. From the theoretical stand-point the model has been based on Petri Net.
Development of vehicle transshipment at European ports
Ongoing globalization causes increasing transportation rates and transshipment volumes at sea ports (Steenken, 2004). Different to container transshipment, the transshipment of finished vehicles has received only minor attention in research yet (Mattfeld and Kopfer, 2003). By means of statistics for major ports of the North-West European coast line the structure and development of vehicle transshipment is outlined. It is shown that a concentration of transshipment volume with respect to specific market segments is taking place. Hub and spoke structures, as already common for container transportation, have not yet been implemented.
Optimising yard operations in port container terminals
This paper deals with the problem of positioning containers in a yard block of a port container terminal. The objective of the container positioning problem (CPP) is to minimise the total handling time in the block, i.e. the time required for storage and reshuffling of containers. One of the constraint types, concerning the last-in first-out (LIFO) principle, implies major modelling challenges. A mixed-integer linear programming model for the general CPP is formulated, implemented in the modelling tool Mosel, and validated by the solution of a test case using the Xpress-MP solver.
Vehicle trajectories random field traffic representation
In the paper novelty vehicle trajectories random field (VTRF) traffic representation dedicated to networked hard real-time traffic control systems is presented and illustrated by PIACON control method. It is emphasized that existing multiple type high spatial resolution satellite and air based imagery together with conventional video, laser, GPS, probe-vehicles technologies are sufficient for VTRF estimation and prediction. Many advantages of VTRF proposal unattainable by conventional traffic models in the area of traffic control, surveillance and management problems are presented. The VTRF cases of spatio-temporal traffic random fields automatically selected by area traffic situation markers are illustrative for PIACON method.
Dynamic calibration approach for delayed car-following models
Microscopic simulation models have become widely applied tools in traffic engineering. Nevertheless, parameter identification remains a difficult tasks due to the fact that parameters are often not directly observable from common traffic data, but also because real driving behavior is variable in time and space, etc. This paper puts forward a new approach to identifying changing parameters of delayed car-following models, including the reaction time. The approach is based on the particle filter approach, and is generalized to enable estimation of reaction times. Besides the methodological contribution, we show empirical evidence for changing driving behavior by applying the approach to microscopic traffic data collected using remote sensing.
Path searching and filtering for network simulation tools aimed at robustness analysis
Traffic simulation models dealing with road networks are already available for several years. Most of them include procedures to distribute traffic over alternative routes between an origin and destination. However, most of these tools are not capable to include ADAS and route guidance systems realistically. In addition, the interest in the design of reliable and robust networks is growing, while a tool to analyze and quantify these properties is still missing. One important element in such a tool would be the realistic distribution of traffic over logical paths, and the availability of dissimilar alternative paths in case of emergencies. An overview and a new approach are presented in this paper.
A self-learning driving behavior model for microscopic online simulation based on remote sensing and equipped vehicle data
Mostly, microscopic simulation models are calibrated with macroscopic measurement data, like flow and speed, which says nothing about the accuracy of the individual driving behavior of the vehicle – driver combinations. The microscopic online simulator MiOS is extended with a driving behavior model based on equipped vehicle and floating car data. It is designed as a self-learning behavior model.
PIACON-DISCON integrated approach to public transport priority control at traffic signals
Giving priority to buses at traffic intersections is a common practice in busy urban areas. Benefit for buses results from reduction of their journey times and improving their service reliability. However the negative impacts of such priorities for other intersection user’s e.g. individual traffic may exceed the buses benefits. In the paper two-level dynamic intelligent traffic control feedback approach is proposed. At the upper level the multi-criteria PIACON control method trade-offs the costs and benefits of all intersection users and proposes in real-time priority option (no-priority is also an option). At the bottom level dynamic dispatching control method DISCON realize priority control mode with PIACON reference input. The presented approach is illustrated by many practical examples realized in new ITS systems environment.
An intermodal traffic control strategy for private vehicle and public transport
This paper proposes a traffic-responsive urban traffic control strategy allowing a real time passive public transport priority. The proposed strategy is based on a store and forward modeling of both of the private vehicle and Public transport traffic. The regulator is designed using the linear quadratic, which allows a traffic responsive co-ordinated control for wide-area networks. The objective of this strategy is to control the junctions traffic lights in order to improve the traffic performance on the sections at the precise times when public transport is using the service sections. A simulation example is provided to demonstrate the efficiency of the proposed strategy.
DREAMS: an integrated information management system for traditional and innovative mobility services in Milan, Italy
This paper presents DREAMS, a web-based integrated information and management system for mobility services in urban areas, designed specifically for the city of Milan, Italy. The core of the system is the travel planner module, which proposes a set of travel solutions for a specific trip taking into account traditional and innovative mobility services. Within this system, we developed two software tools to plan and manage dial-a-ride and car pooling services. We describe in particular the second software, which can be useful especially for company mobility managers and area mobility managers.
Introduction to a node management model for traffic networks: a mesoscopic approach
This study purposes the dynamic mesosimulation of within-day fluctuation of traffic flow in respect to node management rules. Like existing mesosimulation models, the proposed model traces explicitly the vehicles’ movements, and considers aggregate link performances in a dynamic traffic assignment framework. The innovative approach consists in the fact that the model considers the vehicles’ acceleration; therefore, the speed of vehicles is not an average, but a punctual value that allows a more accurate and more precise calculation of flow characteristics. At first, the model has been studied for a single link; afterwards, node management rules have been studied for a network model. In the last stage, the model has been tested on a real network. The model is useful to simulate undercapacity utilisation of networks, such as bottleneck sections, and problems at operative and tactical level.
A delayed flow intersection model for dynamic traffic assignment
Day-to-Day and Within-Day dynamics are classically observed in dynamic traffic assignment, but smaller ones due to traffic lights phases also occur. These micro variations induce flow fluctuations defined at a cycle time scale. Their precise knowledge is irrelevant in a dynamic traffic assignment context. We propose to integrate these micro dynamics into a new intersection model without stages in which their average effects must be taken into account, especially delay and flow restriction generated by the presence of traffic lights.
Theoretical analysis of the efficency of ramp metering, speed management based on Braess-like paradoxes
The paper investigates the origin of the gains resulting from ramp metering and speed management. Similar to Braess's paradox, both traffic control methods reduce the nominal capacity in order to achieve gains. Ramp metering and speed control are shown to prevent capacity drops from which the system is unable to recover, due to hysteresis.
Structure of urban traffic coordination in street networks problem
The problem of efficient traffic coordination in urban street networks is carefully studied in the paper. The problem description was simplified as much as possible, by defining minimal set of decision variables and deriving necessary constraints on their values. The structure of feasible solutions is established introducing new basis of street network loops. The software package was worked out to support the inspection process of all possible solutions for rectangular street networks and both crisp and fuzzy parameters.
An atomic Dijkstra algorithm for dynamic shortest paths in traffic assignment
This paper presents an algorithm that solves the "single-source minimum-cost paths for all departure times" problem in the context of dynamic traffic assignment, when arc traversal times and costs are piecewise linear increasing functions of the time of arrival to an arc.
Sensitivity analysis of a combined network equilibrium model
We consider a combined traffic equilibrium model for mode and route choice with elastic demand, stated as an optimization problem. We state a problem for finding sensitivity information on changes in link flows and travel demands with respect to changes in certain design parameters in the model. In the presentation, we state the sensitivity analysis problem, and propose a solution algorithm suitable for solving both the combined model and the sensitivity problem. Numerical results for a small scale example are shown.
Markov mesoscopic simulation model of overflow queues at multilane signalized intersections
This paper analyzes the interdependency between the dynamics of queues at isolated signalized intersections and the lane-changing behavior of vehicles approaching the intersection. A dynamic queuing model based on Markov Chain renewal process is combined with a lane-changing behavior model in order to simulate the vehicle distribution in time. We applied this simulation to a two-lane intersection, showing how queues influence lane changing before the intersection. Finally we study the case including an accumulation lane, showing how the spillback effect can also influence travelers’ lane changing.
A transportation plan strategy for Turkey
The main aim of this paper is to evaluation of a transportation plan strategy for Turkey. For this reason, the objectives, principles and policies are explained at the beginning of the paper. Then, the strengths, weaknesses, opportunities and threats of the transportation plan strategy are clarified using SWOT analysis. At the end of the study, the general evaluation for transportation plan strategy is made.
Policy forecasts using mixed RP/SP models: some new evidence
The application of discrete choice models estimated at the individual level to forecast different transport strategic policies is common practice. However, as long as we move towards more complex demand models their specification as a prediction tool is not immediate. We analyse the problem of forecasting with models estimated with non-linear utility functions and/or mixed revealed preference (RP) and stated preference (SP) data. We analyse how sensitive are predictions to the class of models used, for different transport strategies designed for the metropolitan area of Cagliari.
Car pooling clubs: solution for the affiliation problem in traditional/dynamic ridesharing systems
Traffic congestion and the associated pressure in car parking, that results from growing car ownership, require the study of innovative measures to reduce the number of cars traveling every day to the city centers, specifically single occupant vehicles. Car pooling is a system by which a person shares his private vehicle with one or more people that have common, or aligned destinations. Until now this systems have been applied mainly in the United States and some Northern European Countries but with modest results. Trust between occupants has proven to be essential for car pooling viability. This paper presents the concept of car pooling clubs as a means to affiliate its members, increasing trust between them and at the same time allowing a more flexible matching between the participants.
Introducing social aspects to multi-agent simulations of travel behavior
Common multi-agent simulations aggregate the behavior of autonomous agents. Better understanding of social aspects of travel behavior may improve the development of multi-agent simulations. In this paper some basic aspects of social behavior are demonstrated using the results of a lab experiment.
Observations overtaking manoeuvres on bi-directional roads
Observations of overtaking manoeuvres on two-lane rural roads were carried out to enhance the understanding of driver behaviour prior to, during and after an overtaking manoeuvre. An instrumented vehicle was driven with different speeds while other vehicles’ overtaking manoeuvres were recorded and analysed afterwards. The differences in duration of overtaking manoeuvres between different overtaking strategies and different speeds of the vehicle that was overtaken, turned out to be small. Fairly short perception-reaction times were observed, indicating that the decision to perform an overtaking manoeuvre is made before an appropriate gap in the oncoming traffic stream is available.
Collecting activity-travel diary data by means of a hand-held computer-assisted data collection tool
Activity-based transportation models have set the standard for modelling travel demand for the last decade. It seems common practice nowadays to collect the data to estimate these activity-based transportation models by means of activity diaries. This paper explores potential advantages and disadvantages that may occur in the collection of this type of data by means of a hand-held computer-assisted data collection tool.
Agent-based modelling of a social dilemma in mode choice based on travelers' expectations and social learning mechanisms
This study attempts to apply an agent-based approach to modelling travel behaviour. A social dilemma situation of travel mode choice is modelled and viewed as a complex system by considering psychological and sociological aspects, which are represented by individuals’ expectations and social learning mechanisms. We apply an imitation game in order to evolve the decision making rules of each traveller. The study reveals some informed insights for resolving the social dilemma, such as the conditions that make cooperation as a possible outcome. Some behaviour and policy implications are also discussed in this paper.
Calibration of a traffic microsimulation model as a tool for estimating the level of travel time variability
A low level of day-to-day variations in travel time is a major feature of a reliable transport system. There is a growing need for credible tools that can predict the extent of travel time variability. We present methodology for using a traffic microsimulation model as such tool, through a special calibration procedure. Various issues, relating to the variability of simulation outputs and to the concept of using this variability to replicate observed travel time fluctuations, are discussed. To test the proposed calibration methodology, its ability to reproduce various distributions of travel times is examined.
An investigation of urban arterial travel time variability
Although a large amount of research has been done on travel time estimation and prediction, research into the variability of travel time and into models describing or explaining this variability is still limited and mainly focused on freeways. This paper uses a fuzzy k-means method to classify urban traffic patterns and investigates the variability of urban arterial travel time as a function of these different traffic patterns. A simulation scenario and empirical data are used to evaluate this method and provide insight into the variability of urban arterial travel time.
The impact of dynamic navigation on the travel times in urban networks
This paper studies the impact of dynamic navigation on the traffic process, especially in urban areas. Simulation studies are focused on the correlation of route choice behaviour, fractions of dynamically navigated vehicles, re-routing frequencies, and travel time reductions. The aim is to identify if already provided travel time information could be regarded as traffic management, and as a consequence, the main objective is to provide drivers with a database of the traffic state which is as large and accurate as possible.
Real-time modeling travel time reliability on freeway
Real-time travel time reliability information has gained more and more attention by researchers, practitioners and travelers. This paper presents travel time reliability as the probability that a certain trip can be made successfully within a specified interval of time as a function of prevailing on-trip traffic conditions, particularly traffic density. A two-dimensional graphical approach allows for intuitive interpretation of changes in travel time reliability at varied levels of route-based density at different levels of service. The latter is interpreted as a travel time threshold differentiating reliable and unreliable trips, the result is a reliability performance measure of freeways, which can be measured and used in real-time.
A variable fixing heuristic for the multiple-depot integrated vehicle and crew scheduling problem
This paper proposes a heuristic solution approach for solving multiple-depot integrated vehicle and crew scheduling problem. The basic idea of the method is to first solve independent vehicle and crew scheduling problems separately, and then identify sequences of trips presented in both solutions. Afterwards, the model size is reduced by fixing such sequences before solving the actual multiple-depot integrated vehicle and crew scheduling problem.
Branch-and-price for integrated multi-depot vehicle and crew scheduling problem
We propose a branch-and-price algorithm to solve the integrated multi-depot vehicle and crew scheduling problem. An integer mathematical formulation that combines a multicommodity network flow model with a set partionning model is presented. We solve the corresponding linear relaxation using a column generation scheme. Two branching strategies are tested over benchmark instances available in the Internet. Computational results show the effectiveness of our approach.
Improved dynamic programming for the vehicle routing problem with time windows
In this paper I propose a Branch-and-Price algorithm for the solution of the Vehicle Routing Problem with Time Windows where the pricing subproblem, the resource constrained elementary shortest path problem (RCESPP), is solved to optimality.
Incorporating parametric action decision trees in computational process models of activity-travel behavior: theory and illustration
As an alternative to utility-maximizing nested-logit models, Albatross uses decision trees to predict the activity-scheduling decisions of individuals and households. The decision trees are derived from activity-diary data and are able to account for discontinuous and non-linear effects of independent variables on choice variables. A potential disadvantage of rule-based models is that the sensitivity of predictions of travel demand may be reduced. To overcome this problem and combine the specific strengths of the rule-based and parametric modeling approaches, the authors have developed a hybrid approach referred to as parametric decision trees. The paper describes the approach and results of incorporating the extended decision trees in Albatross to improve the sensitivity of the model for travel-time and travel-costs scenarios.
The sensitivity of activity-based models of travel demand: results in the case of Albatross
The concept of activity-based models was introduced as an alternative to existing trip-based and tour-based models a few decades ago. Potentially, activity-based models are able to predict individuals’ secondary responses, i.e. re-scheduling of activities, as well as primary responses to changes in transport and land-use systems. In addition, the models are sensitive to changes affecting the time budgets of people. Little is known about the extent to which activity-based models come up to this promise. In this paper, we report the results of scenario analyses conducted to test the sensitivity analysis of the activity-based model Albatross.
A self-learning-process based decision support system for Beijing traffic management
A Self-Learning-Based Decision Support System (DSS) is being developed for Beijing city in China. The inspiration is to be able to propose a best suitable measures for a given (either recurrent or non-recurrent) traffic situation, and to apply it to a real-life traffic management. A major concern is to be able to quickly recognise problems and recommend/retrieve corresponding solutions. To achieve this, 3 major steps are being followed: (1) a matching rule enables to propose a robust solution, against a problem; (2) further search continues to identify a most likely scenario that has been successfully executed before; and (3) most successful scenarios can be prepared offline and stored to a relational database after being tested. This paper proposes a novel self-learning approach using conjointly expert knowledge-based choice and case-based reasoning. Key aspects to support such process include: (a) problem identification that is based on a mesoscopic large-scale network dynamic simulation; and (b) measure evaluation that can be performed according to performance indictors. Effective scenarios (measure to problem) are stored into KBEST (knowledge-based expert system) and made available for offline and online calls. An implementation of such system to incident management is foreseen and being designed.
A decision support system for management of waste lube oils recycling operations
This paper presents a Decision Support System (DSS) for Waste Lube Oils Recycling Operations. The proposed DSS enables dispatchers-schedulers to approach reverse logistical problems, interactively. The DSS incorporates intra-city Heterogenous Fixed Fleet Vehicle Routing with practical and complex operational constraints as well as monitoring of complex waste lube oil reverse collection operations. The DSS generates routes that satisfy all model constraints using artificially intelligence-based optimization methods, innovative wireless telecommunication facilities and GIS technology, all integrated within an ERP framework.
Operational analysis of space transportation system architectures through knowledge and simulation based modeling
This paper describes a combination of simulation and knowledge based assessment models used in the operational analysis of future space transportation systems. The model uses knowledge based logic as estimating relationships combined with a process database to estimate the appropriate ground processes, their duration, and their variability. The developed process model is used to populate a simulation model of the transportation system. Use of the simulation model allows the estimation of operational measures of performance such as labor, cycle time and flight rate.
COSIMA-DSS evaluation system: a new decision support system for large-scale transport infrastructure projects
This paper presents a new decision support model COSIMA-DSS that examines socio-economic feasibility risks involved in the implementation of transport infrastructure projects. The model makes use of conventionally cost-benefit analysis embedded within a wider multi-criteria analysis. The basic approach set out in the paper looks upon the mix between so-called "hard" and "soft" evaluation criteria. Finally, a Monte-Carlo simulation is used to take account of the varying information relating to the different criteria.
Large-scale set partitioning problems: conjectures on the beneficial structure of some real-world instances
In this work we consider large-scale set partitioning problems. Our main purpose is to show that real-world set partitioning problems originating from the container-trucking industry are easier to tackle with respect to general ones. We show such different behavior through computational experiments: in particular, we have applied both a heuristic algorithm and some exact solution approaches to real-world instances as well as to benchmark instances from the Beasley OR-library. Moreover, in order to gain an insight into the structure of the real-world instances, we have performed and evaluated various instance perturbations.
The tabu search heuristic method for a multi vehicle distribution and routing problem
A good quality distribution plan plays a very important role in the transportation process. The vehicle planning and scheduling problem for many cities and vehicles is known to be NP-hard. Real-life vehicle routing problems for furniture distribution impose additional requirements on goods and pallet placements on trucks. The aim of this paper is to present a combination of modern heuristics to generate a feasible distribution plan for real furniture distribution.
A multiperiod expected covering location model for dynamic redeployment of ambulances
Emergency response administrators often face the difficult task of locating a limited number of ambulances in a manner that will yield the best service to a constituent population. In this study we try to determine the minimum number of ambulances that meet or exceed a predetermined coverage requirement for dynamic redeployment of ambulances in response to fluctuating demands throughout the week, depending on the day of week, and even the time of day. We introduce an incremental search algorithm to solve the model and evaluate the effectiveness of our model within the framework of an experimental design
A web-based traffic information system using wireless communication techniques
This paper presents a procedure for developing a web-based traffic information system for Sharjah, United Arab Emirates. The system provides expected travel time and distance between an origin and a destination within, which are calculated based on the shortest path. The input data to the system includes the road network characteristics data, which are provided via a database that is hosted on a server and SMS messages that provide the current traffic status in real-time. The real-time travel time data communication component depends primarily on a GSM wireless communication component.
Opportunities for ITS to improve the reliability of traffic and transport systems in industrial and urbanized areas
This paper describes the results from an exploratory study that assessed the reliability of the Port of Rotterdam transport system. The study was to a considerable extent based on obtaining available knowledge through interviews and a workshop. This research method is assessed and its results are discussed. It appears that the acquired knowledge strongly represents current interests and concerns of involved professionals. It is argued that reliability issues require new developments in ITS, specifically for non-recurrent, rare conditions, more so than is reflected by the discussions with the interviewed professionals
Road and traffic sign detection and recognition
This paper presents an overview of the road and traffic sign detection and recognition. It describes the characteristics of the road signs, the requirements and difficulties behind road signs detection and recognition, how to deal with outdoor images, and the different techniques used in the image segmentation based on the colour analysis, shape analysis. It shows also the techniques used for the recognition and classification of the road signs. Although image processing plays a central role in the road signs recognition, especially in colour analysis, but the paper points to many problems regarding the stability of the received information of colours, variations of these colours with respect to the daylight conditions, and absence of a colour model that can led to a good solution. This means that there is a lot of work to be done in the field, and a lot of improvement can be achieved. Neural networks were widely used in the detection and the recognition of the road signs. The majority of the authors used neural networks as a recognizer, and as classifier. Some other techniques such as template matching or classical classifiers were also used. New techniques should be involved to increase the robustness, and to get faster systems for real-time applications.
Impact of budget constraints on weekly activity patterns of road users
The content of this paper is about a model to simulate weekly activity plans of road users and to find out under which conditions changes of activity patterns occur. In the focus of interest is the sensitivity of activity patterns to budget constraints. The budgets of road users are time and cost budgets for mobility. A scheduling approach considering budgets is used to simulate weekly activity patterns. The model will be calibrated on the basis of datasets of the German Mobility Panel (MOP).
Impacts of intelligent information systems on transport and the economy – the micro-based modelling system OVID
This paper gives an overview of the project OVID (http://www.ovid.uni-karlsruhe.de/) launched by the German Ministry of Research and Education (BMBF). The goal of the project is to evaluate the impact of advanced information systems on road transport in a micro-based way. A simulation platform is built up in order to simulate the reactions of consumers and firms on a micro-scale and to find out under which conditions a change of activity patterns or logistic routines occurs. An interim conclusion is, that the expected benefit from pre-trip information can lead to substantial changes of behaviour and improvements of the transport system.
An agent based distributed mircoscopic online simulation model
To cope with the demand for mobility, which will further increase in the future, the infrastructure has to be used more efficiently. Therefore network operation control is needed to interfere with the traffic. The basis of operational control should be an accurate online estimation of the actual traffic situation and a prediction of the future. The microscopic online simulator MiOS will be presented which allows distributed online simulation for real-time operations. Results are shown for a medium size network of the City of Delft.
Philosophical challenges concerning education and career orientation in the ITS area
Today the field of intelligent transportation systems (ITS) is a multi-disciplinary research topic involving subjects of interest from many areas. This interdisciplinary nature of the subject has resulted in a rapid growth of the area and has provided the necessary scope of work for people from different backgrounds. As a result, many interesting and sophisticated solutions within the area have emerged. On the other hand, the enormous growth of ITS houses various philosophical schools and numerous philosophical challenges to which many of us have been quite reluctant to face up to. The paper outlines the various philosophical schools that co-exist within the field of transportation, with particular emphasis on ITS and aim to address the various philosophical challenges that ITS as an area has to offer. Challenges concerning the flexibility of education offered within the area and issues regarding career orientation have been discussed. This can provide a clear idea about the area and may also aid in cutting down the day-to-day challenges that the researchers in transportation face up with.
A procedure for the solution of the urban bus network design problem with elastic demand
In the last years, the sensitive increase of congestion phenomena in the urban areas has produced important changes for the role reserved to the public transport. This should become the main tool to solve urban transport problem. Critical phase for the planning of the public transport system is the network design problem (determination of routes and associated frequencies). This step may affect the performance of the system for the users and the successive planning steps involving the operator costs (bus and driver scheduling). In this paper, authors propose a solving procedure for the urban bus network design problem that explicitly takes into account the elasticity of the demand.
Meta-heuristic algorithms for a transit route design
Since a Bus Transit Route Network (BTRN) design problem leads to have multiple solutions in its nature, some meta-heuristic algorithms such as simulated annealing, genetic and tabu search algorithms have been developed in order to find a global optimum. Suggested approach for BTRN has been compared with the existing benchmark results. We have found that our solution is better than the other ones in some network parameters.
Solving an accessibility-maximization road network design model: a comparison of heuristics
This article presents a study on three heuristics – an add+interchange algorithm (AIA), a basic genetic algorithm (BGA), and an enhanced genetic algorithm (EGA) – developed to help solving an accessibility-maximization interurban road network design model. The main conclusion of the study was that EGA solutions are consistently better than AIA solutions, and that their computing time, though being rather high, grows considerably slower than the computing time of AIA solutions as network size increases. This suggests that the EGA can be especially useful for dealing with very large road networks.
Interactive multi-objective genetic algorithms for the bus driver scheduling problem
Although in its former formulations the Bus Driver Scheduling Problem (BDSP) has been considered as a Set Covering Problem there is in practice some complicating additional constraints, arising from government legislation, union agreements and company’s dependent operational rules. Moreover, costs, quality of service, and the satisfaction of the drivers’ expectations have to be taken into account, making the problem really multi-criteria. By applying Genetic Algorithms (GA), traditional approaches based on the Set Covering model have been extended, allowing the simultaneous consideration of several complex criteria. In our algorithm, a strong interaction with the planner has been promoted, in tuning and refining solutions, and as a way to deal with the multi-criteria character of the problem. Exhaustive experimental evaluation with real problems from different companies has proved that this approach can quickly produce very satisfactory solutions, bringing automatic solutions closer to the planners’ expectations.
Scheduling buses in rural areas
In many rural areas in Germany pupils on the way to school and back are a large if not the largest group of customers. If all schools start more or less at the same time then the bus companies need a high number of vehicles to serve the customer peak in the morning rush hours. In this article we present a mathematical model and a solution algorithm for an integrated coodination of the school starting times and the public bus services. Computational results show that in the test counties a much lower number of buses would be sufficient if the schools start at different times.
Path relinking for multiple objective combinatorial optimization. TSP case study
The paper presents a new metaheuristic algorithm for multiple objective combinatorial optimization based on the idea of path relinking. The algorithm is applied to the traveling salesperson problem with multiple link (arc) costs, corresponding to multiple objectives. The multiple costs may for example correspond to financial cost of travel along a link, time of travel, or risk in case of hazardous materials. The algorithm searches for new good solutions along paths in the decision space connecting two other good solutions. It is compared experimentally to state of the art algorithms for multiple objective TSP.
Calibration of logit modal split models with feed forward back-propagation neural networks
The presented study examines the possibilities of obtaining better logit mode choice models for home-based work trip purpose in Istanbul metropolitan area by calibrating binary logit modal split models with the employment of feed forward back-propagation algorithm trained neural networks. A two-variable logit model with the trip cost and the trip time variables is calibrated to split trips to private car and public transport modes. The calibration data is aggregated at an appropriate level considering the previous studies’ and master plans’ outcomes. Following the neural network calibrations, the two-variable logit model is calibrated with linear regression method. The results were then compared.
Calibration of a conceptual LUTI model based on neural networks
This paper deals with Land-use-Transport-Interaction (LUTI) and presents the calibration of a neural network based LUTI modeling tool. Literature survey reveals that currently used land use transport models are too aggregate in substance to match travel demand models. Therefore, we look for an alternative approach by researching: (i) different solution methods to make LUTI models more applicable; (ii) a sound way to operationalise these solution methods; (iii) a suitable modeling technique to be used in this context; (iv) the calibration of this model. It is concluded Artificial Neural Networks (ANNs) are suitable for LUTI models and that calibration of a data driven LUTI model is possible.
Industrial vehicles park capacity sizing by means of artificial neural networks
Currently, there is a clear trend to concentrate companies in industrial areas around urban centres. As a consequence of this there has been an increase of traffic produced by industrial vehicles that can even saturate the inputs or outputs of a city and sometimes can produce parking problems. Therefore, there is a tremendous necessity for searching park zones for these vehicles, whose capacity must be sized with accuracy. Estimations currently done on behalf of industrial vehicles calculations come from the number of vehicles at this time in a city, without any consideration about the future necessities of an urban centre. Transport flows can be forecasted with the use of new tools such as Artificial Neural Networks, considering growing trends of urban centres, by mean of which sizing of industrial vehicles park capacity can be done with accuracy. Therefore, the project goal pursues to demonstrate the use of Artificial Neural Networks, and particularly the back-propagation algorithm, as a potential tool for transport flows forecasting based on historical data, and finally the application to other areas inside the transport and logistics world, like industrial vehicles sizing.
Identifying congestion patterns with state space neural networks
In this extended abstract we demonstrate that a particular artificial neural network (ANN) model for freeway travel time prediction not only provides accurate results on both synthetic and real data from inductive loops but also provides detailed information on the underlying traffic conditions. We do this by introducing a new expression for the relevance of each neuron and input variable to the so-called state-space neural network (SSNN) output (predicted travel time) and comparing this relevance measure to data (speeds, flows, densities) observed on the freeway route for which the SSNN was trained.
A framework for dynamic and stochastic vehicle routing
Dynamic and stochastic vehicle routing problems are receiving more attention as both algorithms and computing technology advances. The dynamic aspects are important in many applications and research on practical algorithms is an area with increasing activity. We present a framework for representing dynamic and stochastic vehicle routing problems. The framework is intended for use in creating and running benchmark tests. A set of standard benchmarks and formats will further the research and facilitate the comparison of various algorithms.
On generalized OWA approach to support location and routing decisions
While modeling a transportation system one needs to take into account various negative effects of location and routing decisions for several populated spacial units. The minimization of the worst individual effect, the minimax approach, is the simplest solution concept focused on the spatial equity. In this paper we use the conditional means which generalize the worst effect by taking into account the portion of population affected (quantile). Further, aggregating conditional means for various quantiles we get a generalization of the so-called ordered weighted average (OWA) which allows us to model various preferences.
Algorithms for decision making in transportation systems with uncertain knowledge
A two-level transportation system with scheduling of independent, non-preemptive tasks on unrelated moving executors as well as motion control of a group of moving executors performing the tasks is considered. It is substituted by an uncertain one-level system, where execution times of the tasks are not crisp values but they belong to known intervals. In order to solve the problem the robust approach is used which is based on the worst-case relative regret function. The other manufacturing system with transport of a raw material and its distribution among parallel production units is also considered along with the solution algorithm, where uncertain variables are applied.
Stochastic service network design: the importance of taking uncertainty into account
The objective of this paper is to study how important it is to take uncertainty into account in a service network design problem during the planning phase. We look at how a solution based on uncertain demand differs from a solution based on deterministic demand and show that there can be important structural differences between them. Some of these structural differences help hedge against uncertainty, without necessarily increasing the cost of operating such a schedule. We look at how some schedules can be more robust than others due to their greater flexibility.
Analyzing a vehicle routing problem with stochastic demands using ant colony optimization
In this paper the classical Vehicle Routing Problem (VRP) is extended to cover the more realistic case of uncertainty about customer demands. This case is modelled as a VRP with stochastic demands and tackled with a heuristic solution approach based on Ant Colony Optimization (ACO). The main issues studied in this paper are the modelling of the uncertainty (i) in terms of its influence on the performance of the algorithm and (ii) in terms of the structure and quality of the solutions with respect to different risk measures.
Technical diagnostic of a fleet of vehicles using rough sets theory
The authors of the paper concentrate on diagnostic process applied to vehicles utilized in the delivery system of express mail. The paper is focused on evaluation of diagnostic capacity of particular characteristics, reduction of a set of primary applied characteristics to a minimal and satisfactory subset and generation of the maintenance decision rules. The rough sets theory is applied to support diagnostic process, both attributes-based and criteria-based approaches, and the results of computational experiments are compared.
Vehicle routing with regard to traffic prognosis and congestion probabilities
This paper presents a new instance of the Vehicle Routing Problem with Time Windows (VRPTW) with regard to traffic forecasting and traffic congestion probabilities (VRPTWTP). Traffic prognosis is integrated by calculating time-dependent journey times, which rely on both the prognosis data for the anticipated traffic demand of the roadsection considered at a certain time and the probability of the occurrence of a traffic congestion. While computing tractability of the Mixed-Integer-Program increases, significant improvements regarding delivery accuracy and vehicle utilization can be obtained. This research was achieved within the project OVID, launched by the German Ministry of Research and Education.
Fuzzy values for imprecision and flexible constraints in vehicle routing problems
Classical definitions of vehicle routing problems often lack handling of uncertain parameters and flexibility of constraints. The most popular approaches to these aspects are probability distributions for uncertainty and penalty-based goal function for flexibility. In this paper a different view is proposed: fuzzy sets framework, modeling both imprecision and flexibility. Theoretical considerations are presented and some practical implications are shown.