A conditional β-mean approach to risk-averse stochastic multiple allocation hub location problems

Ghaffarinasab N., Kara B. Y.

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, vol.158, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 158
  • Publication Date: 2022
  • Doi Number: 10.1016/j.tre.2021.102602
  • Journal Name: TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Business Source Elite, Business Source Premier, Communication Abstracts, EconLit, Geobase, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Middle East Technical University Affiliated: No

Abstract

This paper addresses risk-averse stochastic hub location problems where the risk is measured using the conditional p-mean criterion. Three variants of the classical multiple allocation hub location problem, namely the p-hub median, the p-hub maximal covering, and the weighted p-hub center problems are studied under demand data uncertainty represented by a finite set of scenarios. Novel mixed-integer linear programming formulations are proposed for the problems and exact algorithms based on Benders decomposition are developed for solving large instances of the problems. A large set of computational tests are conducted so that the efficiency of the proposed algorithms is proved and the effect of various input parameters on the optimal solutions is analyzed.