A set of efficient heuristics and meta-heuristics to solve a multi-objective pharmaceutical supply chain network

Goodarzian, Fariba; Kumar, Vikas; Ghasemi, Peiman

Abstract

In this paper, we propose a new multi-objective optimization approach for the pharmaceutical supply chain network (PSCN) design problem to minimize the total cost and the delivery time of pharmaceutical products to the hospital and pharmacy, while maximizing the reliability of the transportation system. A new mixed-integer non-linear programming model was developed for the production-allocation-distribution-inventory-ordering-routing problem. Three new heuristics (H-1), (H-2), and (H-3) have been proposed and to validate the model, two new meta-heuristic algorithms, namely, an Improved Social Engineering Optimization (ISEO) and Hybrid Firefly and Simulated Annealing Algorithm (HFFA-SA) have been developed. The proposed mathematical model has been evaluated through extensive simulation experiments by analyzing different criteria. The results show that the proposed model along with the solution method provides a reliable and powerful instrument to solve the PSCN design problem.

Citation

Goodarzian, F., Kumar, V., & Ghasemi, P. (2021). A set of efficient heuristics and meta-heuristics to solve a multi-objective pharmaceutical supply chain network. Computers and Industrial Engineering, 158, Article 107389. https://doi.org/10.1016/j.cie.2021.107389

• Journal Article Type: Article
• Acceptance Date: May 4, 2021
• Online Publication Date: May 7, 2021
• Publication Date: Aug 1, 2021
• Deposit Date: May 4, 2021
• Publicly Available Date: Nov 8, 2022
• Journal: Computers and Industrial Engineering
• Print ISSN: 0360-8352
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 158
• Article Number: 107389
• DOI: https://doi.org/10.1016/j.cie.2021.107389
• Keywords: Pharmaceutical supply chain network; Heuristic algorithms; Improved Social Engineering Optimization; Hybrid Firefly and Simulated Annealing Algorithm; multi-objective optimization
• Public URL: https://uwe-repository.worktribe.com/output/7338015