An outer approximation algorithm for the robust shortest path problem

Mehrdad Shahabi, Avinash Unnikrishnan and Stephen D. Boyles

Transportation Research Part E: Logistics and Transportation Review, 2013, vol. 58, issue C, 52-66

Abstract: This paper describes a new algorithm for the stochastic shortest path problem where path costs are a weighted sum of expected cost and cost standard deviation. We allow correlation between link costs, subject to a regularity condition excluding unbounded solutions. The chief complication in this variant is that path costs are not an additive sum of link costs. In this paper, we reformulate this problem as a conic quadratic program, and develop an outer-approximation algorithm based on this formulation. Numerical experiments show that the outer-approximation algorithm significantly outperforms standard integer programming algorithms implemented in solvers.

Keywords: Robust shortest path; Mean – standard deviation objective; Outer approximation (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (15)

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DOI: 10.1016/j.tre.2013.07.002

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