Document Type
Article
Publication Date
2010
Publication Title
European Journal of Operational Research
Volume
201
Issue
2
First Page
463
Keywords
Experiment/theoretical treatment, Computers, Transportation management, Management science/operations research
Last Page
469
Abstract
Bounding the inefficiency of selfish routing has become an emerging research subject. A central result obtained in the literature is that the inefficiency of deterministic User Equilibrium (UE) is bounded and the bound is independent of network topology. This paper makes a contribution to the literature by bounding the inefficiency of the logit-based Stochastic User Equilibrium (SUE). In a stochastic environment there are two different definitions of system optimization: one is the traditional System Optimum (SO) which minimizes the total actual system travel time, and the other is the Stochastic System Optimum (SSO) which minimizes the total perceived travel time of all users. Thus there are two ways to define the inefficiency of SUE, i.e. to compare SUE with SO in terms of total actual system travel time, or to compare SUE with SSO in terms of total perceived travel time. We establish upper bounds on the inefficiency of SUE in both situations.
DOI
10.1016/j.ejor.2009.03.023
Recommended Citation
Guo, Xiaolei; Yang, Hai; and Liu, Tian-Liang. (2010). Bounding the inefficiency of logit-based stochastic user equilibrium. European Journal of Operational Research, 201 (2), 463-469.
https://scholar.uwindsor.ca/odettepub/46
Comments
NOTICE: this is the author’s version of a work that was accepted for publication in the European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in the European Journal of Operational Research, 201 (2), 2010 and is available here.