A hybrid cross entropy algorithm for solving dynamic transit network design problem
Networking and Internet Architecture
2012-11-26 v1 Artificial Intelligence
Abstract
This paper proposes a hybrid multiagent learning algorithm for solving the dynamic simulation-based bilevel network design problem. The objective is to determine the op-timal frequency of a multimodal transit network, which minimizes total users' travel cost and operation cost of transit lines. The problem is formulated as a bilevel programming problem with equilibrium constraints describing non-cooperative Nash equilibrium in a dynamic simulation-based transit assignment context. A hybrid algorithm combing the cross entropy multiagent learning algorithm and Hooke-Jeeves algorithm is proposed. Computational results are provided on the Sioux Falls network to illustrate the perform-ance of the proposed algorithm.
Cite
@article{arxiv.1211.5371,
title = {A hybrid cross entropy algorithm for solving dynamic transit network design problem},
author = {Tai-Yu Ma},
journal= {arXiv preprint arXiv:1211.5371},
year = {2012}
}