Multi-objective metaheuristics for hub location problem: A case study of rail network planning

• Pham Van, Nam ^[1] ; Nguyen Dang, Nha ^[1] ; Sangsawang, Ornurai ^[2] ; Chanta, Sunarin ^[2]
  1. [1] Vietnam-Korea University of Information and Communication Technology
  2. [2] King Mongkut’s University of Technology North Bangkok
• Localización: Journal of Industrial Engineering and Management, ISSN-e 2013-0953, Vol. 18, Nº. 3, 2025 (Ejemplar dedicado a: In process), págs. 577-593
• Idioma: inglés
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• Resumen

  • Purpose: Hub location problems have been utilized in various applications including rail transportation network planning, where hub serves as a key transit point within the network. In this paper, we focus on determining the optimal location for a rail transportation hub, where cost and service are trade-off.

    Design/methodology/approach: The problem is formulated as a multi-objective programming model with the objectives of minimizing total transportation costs and minimizing maximum travel time. A case study of rail transportation network hub planning in Thailand is presented. Given the complexity and large scale of the real-world case study, we develop and compare the Multi-Objective Tabu Search (MOTS) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to solve the problem.

    Findings: The proposed algorithms yield efficient performance in terms of computational time and solution quality. Performance comparison is further analyzed to see the difference in both algorithms.

    Originality/value: The results offer valuable managerial insights for decision-makers in rail transportation hub network design.