Social welfare analysis of investment public-private partnership approaches for tansportation projects

This paper has two objectives: (1) to introduce a new approach to gaining widespread support for comprehensive road pricing; and (2) to develop a detailed social welfare analysis for road pricing schemes. We first describe a new approach to garnering support for system-wide road pricing, which we refer to as an investment public-private partnership, or IP3. This approach returns a significant portion of the economic value created by road pricing back to its citizen-owners. Next, we present a social welfare framework that estimates the benefits and costs of using the IP3 approach on an urban transportation network. Policy makers typically evaluate public-private partnership (P3) projects using Value for Money (VfM) analysis. However, a P3 project's impact on overall social welfare provides a more comprehensive evaluation criterion. Apart from several theoretical studies, a detailed social welfare analysis that includes all major P3 project stakeholders is lacking. Using Fresno City's transportation system as our case study, we show that system-optimal tolling scenarios favor average users, but that government¿and consequently taxpayers¿would pay for costly tolling systems. In contrast, unlimited profit-maximizing tolls raise substantial profits for government, for the infrastructure's citizen-owners, and for the private sector, but the average user is worse off. From a social welfare perspective, one should search for a Pareto-improvement under which all major stakeholders are better off. Our estimates indicate that a mixed private and public tolling scheme offers such an improvement. A mixed scheme results in the highest social welfare among all scenarios unless the weight placed on motorists' (i.e., transportation users') welfare is very low or the weight placed on residents' welfare is very high relative to the weight of other stakeholders

A biologically inspired network design model

A network design problem is to select a subset of links in a transport network that satisfy passengers or cargo transportation demands while minimizing the overall costs of the transportation. We propose a mathematical model of the foraging behaviour of slime mould P. polycephalum to solve the network design problem and construct optimal transport networks. In our algorithm, a traffic flow between any two cities is estimated using a gravity model. The flow is imitated by the model of the slime mould. The algorithm model converges to a steady state, which represents a solution of the problem. We validate our approach on examples of major transport networks in Mexico and China. By comparing networks developed in our approach with the man-made highways, networks developed by the slime mould, and a cellular automata model inspired by slime mould, we demonstrate the flexibility and efficiency of our approach

A Metaheuristic Framework for Bi-level Programming Problems with Multi-disciplinary Applications

Bi-level programming problems arise in situations when the decision maker has to take into account the responses of the users to his decisions. Several problems arising in engineering and economics can be cast within the bi-level programming framework. The bi-level programming model is also known as a Stackleberg or leader-follower game in which the leader chooses his variables so as to optimise his objective function, taking into account the response of the follower(s) who separately optimise their own objectives, treating the leader’s decisions as exogenous. In this chapter, we present a unified framework fully consistent with the Stackleberg paradigm of bi-level programming that allows for the integration of meta-heuristic algorithms with traditional gradient based optimisation algorithms for the solution of bi-level programming problems. In particular we employ Differential Evolution as the main meta-heuristic in our proposal.We subsequently apply the proposed method (DEBLP) to a range of problems from many fields such as transportation systems management, parameter estimation and game theory. It is demonstrated that DEBLP is a robust and powerful search heuristic for this class of problems characterised by non smoothness and non convexity

Peer evaluation of multi-attribute analysis techniques: Case of a light rail transit network choice

This paper attempts to present a method for differentiating between multi-attribute decision procedures and to identify some competent procedures for major decision problems, where a matrix of alternative-measure of effectiveness and a vector of weights for the latter are available. In this respect, several known multi-attribute analysis procedures are chosen, and the same procedures are exploited to evaluate themselves, based on some evaluation criteria. This is done from an engineering viewpoint and in the context of a transportation problem, using a real case light rail transit network choice problem for the City of Mashhad, and the results are presented. Two concepts have been proposed in this respect and used in this evaluation; peer evaluation and information evaluation, which are investigated in this paper. In the evaluation of five multi-attribute decision procedures, based on nine criteria, and with the help of these procedures themselves in the context of the case under study, the results revealed that these procedures found Electre, Linear Assignment, Simple Additive Weighting, TOPSIS, and Minkowski Distance better than others, in the same order as given. This is backed by a wide range of sensitivity analyses. Nevertheless, despite specific conclusions made regarding the better decision procedures among those evaluated, this paper finds its contribution mainly in the approach to such evaluations and choices