Robust solution for a minimax regret hub location problem in a fuzzy-stochastic environment

Saeid Abbasi-Parizi, Majid Aminnayeri, Mahdi Bashiri

Research output: Contribution to journalArticle

Abstract

In the present paper, a robust approach is used to locate hub facilities considering network risks. An additional objective function, minimax regret, is added to the classical objective function in the hub location problem. In the proposed model, risk factors such as availability, security, delay time, environmental guidelines and regional air pollution are considered using triangular fuzzy-stochastic numbers. Then an equivalent crisp single objective model is proposed and solved by the Benders decomposition method. Finally, the results of both Benders decomposition and commercial optimization software are compared for different instances. Numerical instances were developed based on the well-known Civil Aeronautics Board (CAB) data set, considering different levels of uncertainty in parameters. The results show that the proposed model is capable of selecting nodes as sustainable hubs. Also, the results confirm that using Benders decomposition is more efficient than using classical solution methods for large-scale problems.

Original languageEnglish
Pages (from-to)1-25
Number of pages25
JournalJournal of Industrial and Management Optimization
Volume13
Issue number5
DOIs
Publication statusPublished - 1 Jun 2018
Externally publishedYes

Keywords

  • Benders decomposition algorithm
  • Hub location
  • Minimax regret
  • Robust optimization

ASJC Scopus subject areas

  • Business and International Management
  • Strategy and Management
  • Control and Optimization
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Robust solution for a minimax regret hub location problem in a fuzzy-stochastic environment'. Together they form a unique fingerprint.

  • Cite this