Distributionally robust maximum probability shortest path problem

Rashed Khanjani-Shiraz (), Ali Babapour-Azar (), Zohreh Hosseini-Noudeh () and Panos M. Pardalos ()
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Rashed Khanjani-Shiraz: University of Tabriz
Ali Babapour-Azar: University of Tabriz
Zohreh Hosseini-Noudeh: University of Tabriz
Panos M. Pardalos: University of Florida

Journal of Combinatorial Optimization, 2022, vol. 43, issue 1, No 8, 140-167

Abstract: Abstract In this study, we discuss and develop a distributionally robust joint chance-constrained optimization model and apply it for the shortest path problem under resource uncertainty. In sch a case, robust chance constraints are approximated by constraints that can be reformulated using convex programming. Since the issue we are discussing here is of the multi-resource type, the resource related to cost is deterministic; however, we consider a robust set for other resources where covariance and mean are known. Thus, the chance-constrained problem can be expressed in terms of a cone constraint. In addition, since our problem is joint chance-constrained optimization, we can use Bonferroni approximation to divide the problem into L separate problems in order to build convex approximations of distributionally robust joint chance constraints. Finally, numerical results are presented to illustrate the rigidity of the bounds and the value of the distributionally robust approach.

Keywords: Robust shortest path; Joint chance constrained; Bonferroni approximation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10878-021-00747-9

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