Enhancing optimization models for multi-commodity sustainable supply chain networks and managing environmental challenges


Wang Z., Ala A., Simic V., PAMUCAR D., AYDIN N.

Operational Research, vol.26, no.1, 2026 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 26 Issue: 1
  • Publication Date: 2026
  • Doi Number: 10.1007/s12351-025-01010-3
  • Journal Name: Operational Research
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, zbMATH
  • Keywords: Design and planning, Environmental management, Multi-Layer supply chain, Optimization approaches, Sustainability
  • Azerbaijan State University of Economics (UNEC) Affiliated: Yes

Abstract

The significance of multi-commodity sustainable supply chain issues is highlighted by various factors, such as environmental considerations, meeting customer expectations, and organizational financial reasons. This research presents a new multi-commodity supply chain network to decrease the network’s total costs and reduce emissions of environmental problems to reach to sustainability objective. The sectors in the presented approach include recovery and recycling units for parts as well as suppliers, producers, distribution centers, warehouses, and customers. A computational model is also developed for the suggested issue. Additionally, the implemented model is resolved on small and medium scales by utilizing weighted goal programming, and two metaheuristic algorithms are included in the non-dominated sorting genetic algorithm-II (NSGA-II). Particle swarm optimization (PSO) approaches can be utilized on large scales for research. Finally, numerical outcomes show that the suggested model is more accurate and can resolve the service level and shortage issues. The outcomes demonstrate the proposed PSO algorithm’s superiority over the NSGA-II method by 28% better performance.