Reliable pathfinding problems for a correlated network: A linear programming problem in a hypergraph

Kenetsu Uchida, Yifan Wang and Ryuichi Tani

European Journal of Operational Research, 2025, vol. 326, issue 2, 234-254

Abstract: This study addresses the NP-hard reliable path problem, which seeks the path with minimum travel cost in correlated road networks, formulated as mean-variance (m-v) and mean-standard deviation (m-s) shortest path problems. This study proposes a novel approach that transforms these nonlinear binary integer programming models into standard linear programming (LP) problems using structure-preserving linearization and graph transformation techniques. The resulting LP formulations guarantee global optimality, overcoming the computational challenges of real-world networks. Numerical experiments on real-world networks demonstrate that the proposed method efficiently identifies the globally optimal path, matching the performance of exact methods like branch-and-bound while offering greater model flexibility. These findings provide a scalable and robust framework for reliable path selection in complex transportation networks.

Keywords: Transportation; Reliable path; Stochastic travel time; Hypergraph; Total unimodularity (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:326:y:2025:i:2:p:234-254

DOI: 10.1016/j.ejor.2025.04.046

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