Koh, Andrew (2009) A Coevolutionary Particle Swarm Algorithm for Bi-Level Variational Inequalities: Applications to Competition in Highway Transportation Networks. In: Natural Intelligence for Scheduling, Planning and Packing Problems. Studies in Computational Intelligence (250). Springer , Berlin , pp. 195-217. ISBN 978-3-642-04038-2
A climate of increasing deregulation in traditional highway transportation, where the private sector has an expanded role in the provision of traditional transportation services, provides a background for practical policy issues to be investigated. One of the key issues of interest, and the focus of this chapter, would be the equilibrium decision variables offered by participants in this market. By assuming that the private sector participants play a Nash game, the above problem can be described as a Bi-Level Variational Inequality (BLVI). Our problem differs from the classical Cournot-Nash game because each and every player’s actions is constrained by another variational inequality describing the equilibrium route choice of users on the network. In this chapter, we discuss this BLVI and suggest a heuristic coevolutionary particle swarm algorithm for its resolution. Our proposed algorithm is subsequently tested on example problems drawn from the literature. The numerical experiments suggest that the proposed algorithm is a viable solution method for this problem.
|Copyright, Publisher and Additional Information:||Springer. This is an author produced version of a chapter accepted for publication in 'Studies in Computational Intelligence'. Uploaded in accordance with the publisher's self-archiving policy.|
|Institution:||The University of Leeds|
|Academic Units:||The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds)|
|Depositing User:||MR ANDREW KOH|
|Date Deposited:||19 Oct 2009 14:01|
|Last Modified:||16 Sep 2016 13:48|