Optimal Path Problems with Second-Order Stochastic Dominance Constraints
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This paper studies optimal path problems integrated with the concept of second order stochastic dominance. These problems arise from applications where travelers are concerned with the trade off between the risks associated with random travel time and other travel costs. Risk-averse behavior is embedded by requiring the random travel times on the optimal paths to stochastically dominate that on a benchmark path in the second order. A general linear operating cost is introduced to combine link- and path-based costs. The latter, which is the focus of the paper, is employed to address schedule costs pertinent to late and early arrival. An equivalent integer program to the problem is constructed by transforming the stochastic dominance constraint into a finite number of linear constraints. The problem is solved using both off-the-shelf solvers and specialized algorithms based on dynamic programming (DP). Although neither approach ensures satisfactory performance for general large-scale problems, the numerical experiments indicate that the DP-based approach provides a computationally feasible option to solve medium-size instances (networks with several thousand links) when correlations among random link travel times can be ignored.
KeywordsOptimal path problem Stochastic dominance Dynamic programming Integer programming
Dr. Richard A. Waltz kindly provided a free copy of KNITRO to be used with AMPL. The authors would like to thank Dr. Pattharin Sarutipand from Northwestern University for her assistance with building AMPL models, and Leilei Zhang from University of Illinois at Chicago for her help with numerical experiments and for valuable discussions on the topic of Section 3.4. We also thank three anonymous referees for their constructive comments.
This research was partially supported by National Science Foundation (CMMI-0928577 and CMMI-1033051) and Northwestern’s Center for Commercialization and Innovative Transportation Technology.
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