A multi-objective integrated optimisation model for facility location and order allocation problem in a two-level supply chain network

Amin-Tahmasbi, Hamzeh; Sadafi, Sina; Ekren, Banu Y.; Kumar, Vikas

Abstract

This study proposes a mixed-integer multi-objective integrated mathematical model solving facility location and order allocation optimisation problems simultaneously in a two-echelon supply chain network. The proposed problem is motivated by a factoryless concept and by providing a dynamic decision-making solution under a multi-period time horizon. Within the model, we also determine the optimal replenishment number of production facilities by the multi-objective functions. The multi-objective functions include minimisation of the total cost, rejected and late delivery units and, maximisation of the assessment score of the selected suppliers. The studied dynamic decision model is significant for the cost-efficient management of companies’ supply chain networks. The mixed-integer mathematical model is developed by the LP-metric method and it is solved by the GAMS optimisation software. Due to the NP-hard structure of the problem, for large-scale instances, we utilise the Multi-Objective Particle Swarm Optimisation (MOPSO) and Multi-Objective Vibration Damping Optimisation (MOVDO) heuristic solution approaches. Numerical results show that, for large-scale problems, the MOPSO method performs better in Pareto solutions and decreases run times. However, the MOVDO method performs better regarding the Mean Ideal Distance and the Number of Solutions Cover surface criterion. The developed solution approach by this paper is a generic model which can be applied for any two-level network for simultaneous optimisation of supplier selection, location determination of facilities and their replenishment amounts.

Citation

Amin-Tahmasbi, H., Sadafi, S., Ekren, B. Y., & Kumar, V. (2023). A multi-objective integrated optimisation model for facility location and order allocation problem in a two-level supply chain network. Annals of Operations Research, 324, 993–1022. https://doi.org/10.1007/s10479-022-04635-1

• Journal Article Type: Article
• Acceptance Date: Feb 21, 2022
• Online Publication Date: Apr 15, 2022
• Publication Date: May 1, 2023
• Deposit Date: Feb 21, 2022
• Publicly Available Date: Apr 16, 2023
• Journal: Annals of Operations Research
• Print ISSN: 0254-5330
• Electronic ISSN: 1572-9338
• Publisher: Springer (part of Springer Nature)
• Peer Reviewed: Peer Reviewed
• Volume: 324
• Pages: 993–1022
• DOI: https://doi.org/10.1007/s10479-022-04635-1
• Keywords: Supply chain management; Facility location; MOPSO; MOVDO; Supplier selection
• Public URL: https://uwe-repository.worktribe.com/output/9047995
• Publisher URL: https://link.springer.com/article/10.1007/s10479-022-04635-1