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A Coevolutionary Particle Swarm Algorithm for\ud Bi-Level Variational Inequalities: Applications\ud to Competition in Highway Transportation\ud Networks

By Andrew Koh


A climate of increasing deregulation in traditional highway transportation,\ud where the private sector has an expanded role in the provision of traditional\ud transportation services, provides a background for practical policy issues to be investigated.\ud One of the key issues of interest, and the focus of this chapter, would\ud be the equilibrium decision variables offered by participants in this market. By assuming\ud that the private sector participants play a Nash game, the above problem can\ud be described as a Bi-Level Variational Inequality (BLVI). Our problem differs from\ud the classical Cournot-Nash game because each and every player’s actions is constrained\ud by another variational inequality describing the equilibrium route choice of\ud users on the network. In this chapter, we discuss this BLVI and suggest a heuristic\ud coevolutionary particle swarm algorithm for its resolution. Our proposed algorithm\ud is subsequently tested on example problems drawn from the literature. The numerical\ud experiments suggest that the proposed algorithm is a viable solution method for\ud this problem

Publisher: Springer
Year: 2009
OAI identifier: oai:eprints.whiterose.ac.uk:9875

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