A dynamic shortest path algorithm using multi‐step ahead link travel time prediction

In this paper, a multi‐step ahead prediction algorithm of link travel speeds has been developed using a Kalman filtering technique in order to calculate a dynamic shortest path. The one‐step and the multi‐step ahead link travel time prediction models for the calculation of the dynamic shortest path have been applied to the directed test network that is composed of 16 nodes: 3 entrance nodes, 2 exit nodes and 11 internal nodes. Time‐varying traffic conditions such as flows and travel time data for the test network have been generated using the CORSIM model. The results show that the multi‐step ahead algorithm is compared more favorably for searching the dynamic shortest time path than the other algorithm.     

Competitive tendering versus performance-based negotiation in Swiss public transport

The purpose of this study is to assess differences in the levels of cost efficiency of bus lines operated under competitively tendered contracts and performance-based negotiated contracts. Following the revision of the Swiss railways act in 1996, regional public authorities were given the choice between two different contractual regimes to procure public passenger transport services. We directly compare the impact of competitive tendering and performance-based negotiation by applying a stochastic frontier analysis to the complete dataset of bus lines (n = 630) operated by the main Swiss company (Swiss Post) at the same time (in 2009) throughout the country. The overall results show that the differences in the levels of cost efficiency between the two contractual regimes are not significant. Our findings are in line with recent evidence of cost convergence between competitive tendering and performance-based negotiation, and suggest that the practice of using both contractual regimes is challenging for the operators in terms of competitive pressure. The threat of competitive tendering may have a disciplining effect on negotiation since it prevents bus companies from bargaining inadequate rents and inducing asymmetric information advantages.     

Coordination problems in container barging in the port of Rotterdam: an institutional analysis

Container barging has gained in importance in port-related transport along with the need for sustainable transport. Nevertheless, coordination problems between terminal operator and barge operator exist, and performance lags behind. This paper analyses factors that may hinder or stimulate a better future performance of container barging in the port of Rotterdam. A case study is accomplished and guided by a framework rooted in Institutional Economics. Despite favourable conditions set by governments and the port authority, the share of container barging has hardly grown. The container barging sector in Rotterdam is embedded in a history with many alliances, a high degree of organisation, and a good track record in the development of institutional arrangements to solve coordination problems. However, the present contractual relations in the transport chain form an inadequate condition. From a theoretical perspective, the paper shows the value of studying port-related transport chains by acknowledging their institutional context.     

A column generation algorithm for the bus driver scheduling problem

Bus driver scheduling aims to find the minimum number of bus drivers to cover a published timetable of a bus company. When scheduling bus drivers, contractual working rules must be enforced, thus complicating the problem. In this research, we develop a column generation algorithm that decomposes this complicated problem into a master problem and a series of pricing subproblems. The master problem selects optimal duties from a set of known feasible duties, and the pricing subproblem augments the feasible duty set to improve the solution obtained in the master problem. The proposed algorithm is empirically applied to the realistic problems of several bus companies. The numerical results show that the proposed column generation algorithm can solve real‐world problems and obtain bus driver schedules that are better than those developed and used by the bus companies. Copyright © 2016 John Wiley & Sons, Ltd.     

Network design: selection and design of links and facility location

In this paper we introduce new network design problems. A network of potential links is given. Each link can be either constructed or not at a given cost. Also, each constructed link can be constructed either as a one-way or two-way link. The objective is to minimize the total construction and transportation costs. Two different transportation costs are considered: (i) traffic is generated between any pair of nodes and the transportation cost is the total cost for the users and (ii) demand for service is generated at each node and a facility is to be located on a node to satisfy the demand. The transportation cost in this case is the total cost for a round trip from the facility to each node and back. We will consider two options in regard to the links between nodes. They can either be two-way only, or mixed, with both two-way and one-way (in either direction) allowed. When these options are combined with the two objective functions, four basic problems are created. These problems are solved by a descent algorithm, simulated annealing, tabu search, and a genetic algorithm. Extensive computational results are presented.     

Application of optimal subset selection to problems of design and scheduling in urban transportation networks

The paper describes some possibilities for modifying the optimal network algorithm developed by Boyce, Farhi and Weischedel in a way that makes it applicable to some practical problems of network planning. The modifications, which have been tested with respect to their effect on the efficiency of the algorithm, include the introduction of asymmetrical demand structures, the integration of an existing network, the lexico-minimization of a dynamic objective function, and the consideration of constraints related to interdependencies between candidate links. Two small network problems and one medium-sized problem (61 nodes, 104 links, 16 candidates) have been computed; the results support the hypothesis that the algorithm may be applied to produce approximate solutions to problems of practical dimensions within a reasonable range of time.     

Do the organizational forms affect passenger satisfaction? Evidence from Chinese public transport service

This paper presents a discussion on the relationship between organizational forms (including the ownership structure and the contractual practices) and passenger satisfaction of Chinese public transport service. To test this proposition, an original rich data set covering 4702 respondents and 58 public transport operators of 13 cities for the period 2013–2014 is used. We firstly estimate the passenger satisfaction based on customer satisfaction theory and PLS-SEM, and then take into consideration the mixed logit model to assess the effect between them. Conclusions drawn from the study are summarized as follows: ① The effect of organizational forms on the passenger satisfaction of public transport service is confirmed. ② Public transport services franchised to public ownership offer higher passenger satisfaction than those franchised to private ownership and mixed ownership. ③ Public transport services regulated by the management contracts incite more passenger satisfaction than those regulated by net cost contracts and gross cost contracts.     

The existence, uniqueness and computation of an arc-based dynamic network user equilibrium formulation

In this paper, a dynamic user equilibrium traffic assignment model with simultaneous departure time/route choices and elastic demands is formulated as an arc-based nonlinear complementarity problem on congested traffic networks. The four objectives of this paper are (1) to develop an arc-based formulation which obviates the use of path-specific variables, (2) to establish existence of a dynamic user equilibrium solution to the model using Brouwer's fixed-point theorem, (3) to show that the vectors of total arc inflows and associated minimum unit travel costs are unique by imposing strict monotonicity conditions on the arc travel cost and demand functions along with a smoothness condition on the equilibria, and (4) to develop a heuristic algorithm that requires neither a path enumeration nor a storage of path-specific flow and cost information. Computational results are presented for a simple test network with 4 arcs, 3 nodes, and 2 origin–destination pairs over the time interval of 120 periods.     

Check-in allocation improvements through the use of a simulation–optimization approach

The aeronautical industry is still under expansion in spite of the problems it is facing due to the increase in oil prices, limited capacity, and novel regulations. The expansion trends translate into problems at different locations within an airport system and are more evident when the resources to cope with the demand are limited or are reaching to theirs limits. In the check-in areas they are appreciated as excessive waiting times which in turn are appreciated by the customers as bad service levels. The article presents a novel methodology that combines an evolutionary algorithm and simulation in order to give the best results taking into account not only the mandatory hard and soft rules determined by the internal policies of an airport terminal but also the quality indicators which are very difficult to include using an abstract representation. The evolutionary algorithm is developed to satisfy the different mandatory restrictions for the allocation problem such as minimum and maximum number of check-in desks per flight, load balance in the check-in islands, opening times of check-in desks and other restrictions imposed by the level of service agreement. Once the solutions are obtained, a second evaluation is performed using a simulation model of the terminal that takes into account the stochastic aspects of the problem such as arriving profiles of the passengers, opening times physical configurations of the facility among other with the objective to determine which allocation is the most efficient in real situations in order to maintain the quality indicators at the desired level.     

Aligning the purchase of green logistics practices between shippers and logistics service providers

This paper explores shippers’ (i.e. logistics buyers) and logistics service providers’ (LSPs) perceptions of green concerns under diverse contractual settings during the key phases of the logistics purchasing process: request for proposal, negotiations, contracting and execution. Accordingly, it derives recommendations that could increase the actors’ inter- and- intra-organisational alignment on green targets throughout these phases. Empirical data are obtained from eight individual cases of three shippers and five LSPs, representing the buyer/seller roles within logistics arrangements. Contrary to previous literature holding the view that setting more green demands by shippers would guarantee green outcomes, the findings show that shippers’ green demands may hinder green logistics applications due to impediments to LSPs’ asset-sharing strategies. Also, a deadlock situation is revealed in the negotiations phase, where both actors await each other to introduce additional demands/offers—calling for further regulatory intervention to release this deadlock. Moreover, this paper shows how a mismatch of interests in contractual periods between shippers and LSPs can obstruct green investments—signalling that the green criterion is not the decisive factor in shaping shippers’ outsourcing strategies. The findings also stress a lack of follow-up efforts by shippers on green measures that were specified pre-contract, attributing this to contrasting intra-organisational objectives within shippers’ firms. This paper contributes to the green logistics purchasing literature by revealing how different contractual settings play an important role in shaping shippers’/LSPs’ perceptions of green concerns during the logistics purchasing process. Further, it is one of the first studies to provide phase-specific recommendations to increase the actors’ alignment on green targets.     

Stochastic optimal path problem with relays

This paper studies the optimal path problem for travelers driving with vehicles of a limited range, such as most battery electric vehicles currently available in the market. The optimal path in this problem often consists of several relay points, where the vehicles can be refueled to extend its range. We propose a stochastic optimal path problem with relays (SOPPR), which aims at minimizing a general expected cost while maintaining a reasonable arrival probability. To account for uncertainty in the road network, the travel speed on a road segment is treated as a discrete random variable, which determines the total energy required to traverse the segment. SOPPR is formulated in two stages in this paper. In the first stage, an optimal routing problem is solved repeatedly to obtain the expected costs and arrival probabilities from any node to all refueling nodes and the destination. With this information, the second stage constructs an auxiliary network, on which the sequence of refueling decisions can be obtained by solving another optimal path problem. Label-correcting algorithms are developed to solve the routing problems in both stages. Numerical experiments are conducted to compare the stochastic and deterministic models, to examine the impact of different parameters on the routing results, and to evaluate the computational performance of the proposed algorithms.     

Heuristic ranking and selection procedures for network design problems

Two heuristic approaches to solving discrete non-linear network design problems and other subset selection problems are described and tested. These heuristics operate similarly to other add, delete and interchange heuristics that have been applied to network design problems. However, the selection criterion adopted here is the ratio of objective function change per unit of resource cost, which other authors have described as an effective gradient measure for zero-one integer programming problems. Optimal branch-and-bound algorithms previously developed and tested are reviewed, and those results serve as benchmarks with which to compare these heuristics described in this paper. The first heuristic ranks and deletes alternative network modifications from an entire set of candidate projects, such as new links or link improvements, until the subset of remaining projects fits within the constraint space. This method was found to achieve optimal or near-optimal solutions to each of the test cases, even when the number of candidate projects deleted in each iteration was increased from one to many. The quality of those results led us to investigate a constrained random sampling procedure in which candidate projects are ranked with regard to randomly generated networks, and a solution is then chosen on the basis of these rankings. This second approach was found to achieve solutions that were almost as good as those obtained with the rank and delete heuristic.     

A dynamic empty equipment and crew allocation model for long-haul networks

This research develops a realistic and efficient operational model to optimize empty equipment and crew movements in long-haul trucking networks with consolidation, where returning drivers home within a reasonable amount of time is an important issue. The problem can be stated as follows. On a network of consolidation centers, demand is expressed as a set of trailer-loads that need to be moved between each pair of consolidation centers in each time period and the objective is to optimize trailer, tractor and driver movements while ensuring that drivers return home within a pre-determined period of time. In this paper, a dynamic integer programming model is developed and an efficient approximate solution method is proposed, which involves column generation and branch-and-bound. The algorithm switches from a combination of network and primal simplex to dual simplex to overcome the degeneracy problem, which is very common for dynamic networks. This novel approach enables solving large problems with many intervals. We solved problems with up to 30 nodes and 48 periods successfully by using real data provided by a less-than-truckload company, and by generating statistical forecasts based on the real data.     

Renegotiating PPP Contracts: Reinforcing the ‘P' in Partnership

Abstract

The issue of renegotiation is becoming increasingly important as a tool to address uncertainty of public private partnership (PPP) projects and as a mechanism to restore its economic and financial equilibrium. This paper aims to understand how and why renegotiations occur in long-lasting PPP projects and what are the pros and cons of the renegotiation. We depart from a literature review on contract incompleteness and on the determinant factors for the renegotiation of infrastructure concessions. To illustrate the discussion, the case studies of nine European PPP projects are analysed by examining the specific exogenous and endogenous determinant factors that conduce to renegotiating contracts. The implications of contractual renegotiations are explained and summarized through a comparison of our case studies with literature. Although renegotiation, per se, is not a solution for the successful implementation of PPP projects, our findings reinforce the idea of contractual flexibility as a tool that allows adapting to uncertainty. Moreover, effective communication mechanisms allow a better response to unforeseen events, reinforcing the partners’ commitment to deliver a win–win project.     

Data-driven optimization of railway maintenance for track geometry

Railway big data technologies are transforming the existing track inspection and maintenance policy deployed for railroads in North America. This paper develops a data-driven condition-based policy for the inspection and maintenance of track geometry. Both preventive maintenance and spot corrective maintenance are taken into account in the investigation of a 33-month inspection dataset that contains a variety of geometry measurements for every foot of track. First, this study separates the data based on the time interval of the inspection run, calculates the aggregate track quality index (TQI) for each track section, and predicts the track spot geo-defect occurrence probability using random forests. Then, a Markov chain is built to model aggregated track deterioration, and the spot geo-defects are modeled by a Bernoulli process. Finally, a Markov decision process (MDP) is developed for track maintenance decision making, and it is optimized by using a value iteration algorithm. Compared with the existing maintenance policy using Markov chain Monte Carlo (MCMC) simulation, the maintenance policy developed in this paper results in an approximately 10% savings in the total maintenance costs for every 1 mile of track.     

Shortest route algorithm with movement prohibitions

This paper presents an algorithm with movement prohibitions which eliminates some problems encountered in network representation used for traffic assignment models, and further allows the representation of the network to be simplified. The paper first presents an appraisal of some proposed methods and reviews the basic concept of existing shortest-route algorithms. The problem of obtaining shortest routes in networks with movement prohibitions is formulated and an algorithm presented. The computational procedure is illustrated by means of a numerical example. The computational efficiency of the algorithm is tested and the test results show that the algorithm is very efficient.     

A fuzzy-logic-based system for freeway bottleneck severity diagnosis in a sensor network

It is essential for local traffic jurisdictions to systematically spot freeway bottlenecks and proactively deploy appropriate congestion mitigation strategies. However, diagnostic results may be influenced by unreliable measurements, analysts’ subjective knowledge and day-to-day traffic pattern variations. In order to suitably address these uncertainties and imprecise data, this study proposes a fuzzy-logic-based approach for bottleneck severity diagnosis in urban sensor networks. A dynamic bottleneck identification model is first proposed to identify bottleneck locations, and a fuzzy inference approach is then proposed to systematically diagnose the severities of the identified recurring and non-recurring bottlenecks by incorporating expert knowledge of local traffic conditions. Sample data over a 1-month period on an urban freeway in Northern Virginia was used as a case study for the analysis. The results reveal that the proposed approach can reasonably determine bottleneck severities and critical links, accounting for both spatial and temporal factors in a sensor network.     

Transformation of transport policy in Great Britain

The British Government recently issued a white paper on its future transport strategy. Its central precept is unambiguous: current trends in traffic are unsustainable, from the point of view of the environment, business efficiency, health, and the unfeasibility of providing growth in road capacity that would keep pace with predicted growth in traffic. Much of the policy logic in the white paper stems from the explicit abandonment of `predict-and-provide' as a desirable — or possible — strategy. This leads to a recognition of the importance of a co-ordinated approach to public transport, walking and cycling, together with policies aimed at reducing less necessary travel where possible; ensuring that the costs of congestion and environmental pollution are, as far as practical, met by those who cause them (in which the revenue from new pricing systems would be kept under local control and used for transport improvements); an emphasis on better maintenance and management of the road system rather than increasing its capacity; consideration of the effects on transport of other policies in land-use, health, education etc; development of institutional structures or contractual arrangements able to bring these changes about; and conditions in which people's everyday behaviour and attitudes may be in harmony with policy, finance and environmental constraints. These themes did not arise out of the blue following the general election in 1997. They evolved over many years, especially in nearly ten years of intense discussion connected with the previous two governments' recognition that the 1989 road programme (`Roads to Prosperity'), in spite of its size and expense, would still not be nearly sufficient to keep pace with traffic growth, as well as being environmentally damaging. The process of discussion and argument has not ceased with publication of the white paper. A very interesting feature of the current debate is that its central argument is widely (though not unanimously) accepted in the media, with great emphasis on the problems of implementation. The author argues that the policy shift is genuine and firmly grounded in research, though with a number of real problems in implementation, research and methodology that will have to be addressed.     

Instantaneous multihop connectivity of one-dimensional vehicular ad hoc networks with general distributions of communication nodes

Connected and automated vehicle technologies hold great promises for improving the safety, efficiency, and environmental impacts of the transportation sector. In this study we are concerned with multihop connectivity of instantaneous vehicular one-dimensional ad hoc networks (VANETs) formed by connected vehicles along a communication path in a road network with given either vehicle locations or traffic densities, market penetration rates, and transmission ranges. We first define a new random variable for the location of the end node of a communication chain, which is a discrete random variable with given vehicle locations and a mixed random variable with given traffic densities. Then recursive, iterative, or differential equation models of instantaneous multihop connectivity between two communication nodes are derived from the relationships between end node probability mass or density function and connectivity. Assuming a simple communication model, the new models are applicable for general distribution patterns of vehicles and communication nodes, including non-evenly placed vehicles and nonhomogeneous Poisson distributions of nodes. With given vehicle locations, the computational cost for this new model is linear to the number of vehicles; with given traffic densities, we derive a new closed-form connectivity model for homogeneous Poisson distributions of communication nodes and an approximate closed-form model when distribution patterns of communication nodes are given by spatial renewal processes. We then apply the models to evaluate impacts on connectivity of traffic patterns, including shock waves, and road-side stations. The connectivity model could be helpful for designing routing protocols in VANETs and developing their applications in transportation systems.