Optimization of production, distribution, natural resources and capacity planning throughout process sector worldwide supply chains with various goals


Yuan J., lv Z., Aliyeva T., Chen X.

Resources Policy, vol.97, 2024 (SSCI) identifier

  • Publication Type: Article / Article
  • Volume: 97
  • Publication Date: 2024
  • Doi Number: 10.1016/j.resourpol.2024.105187
  • Journal Name: Resources Policy
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, International Bibliography of Social Sciences, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Business Source Elite, Business Source Premier, Communication Abstracts, Compendex, EconLit, Index Islamicus, INSPEC, Metadex, PAIS International, Pollution Abstracts, Public Affairs Index, Civil Engineering Abstracts
  • Keywords: Complex, Financial efficiency, Natural resources, Optimization
  • Azerbaijan State University of Economics (UNEC) Affiliated: Yes

Abstract

This study delves into the intricate dynamics of green transformation within global mining and other process industries, focusing on production, distribution, and capacity planning under the framework of the Asian Mineral Vision. By addressing sustainability, resource efficiency, and cost reduction, the research highlights the multifaceted challenges faced by industry participants in achieving green objectives. In addition to financial efficiency, the study emphasizes the importance of customer service quality and responsiveness. To tackle these challenges, we propose a novel multiobjective mixed-integer linear programming (MILP) approach. The model incorporates key goals such as minimizing total cost, total flow time, and total missed sales, reflecting the interconnected nature of financial efficiency, operational agility, and customer satisfaction. To further enhance the model's flexibility, we integrate discrete strategies for plant capacity expansion, recognizing the crucial role of capacity management in responding to evolving demand dynamics. The multiobjective optimization problem is addressed using the lexicographic minimax technique and the ε-constraint method. A comprehensive numerical example illustrates the practical relevance and effectiveness of our proposed model and solution methods, providing valuable insights into improving the resilience and performance of green supply chain networks in the process industry.