Solving a Multi-Item Supply Chain Network Problem by Three Meta-heuristic Algorithms

Document Type: Original Manuscript


1 Young researchers and elite clud, Khalkhal branch Islamic azad university, khalkhal, iran,

2 Islamic Azad University, Qazvin Branch

3 North Karegar Street School of Industrial Engineering, College of Engineering, University of Tehran

4 Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran



The supply chain network design not only assists organizations production process (e.g.,plan, control and execute a product’s flow) but also ensure what is the growing need for companies in a longterm. This paper develops a three-echelon supply chain network problem including multiple plants, multiple distributors, and multiple retailers with amulti-mode demand satisfaction policy inside of production planning and maintenance. The problem is formulated as a mixed-integer linear programming model. Because of its NP-hardness, three meta-heuristic algorithms(i.e., tabu search, harmony search and genetic algorithm) are used to solve the given problem. Also, theTaguchi method is used to choose the best levels of the parameters of the proposedmeta-heuristic algorithms. The results show that HS has abetter solution quality than two other algorithms.

Graphical Abstract

Solving a Multi-Item Supply Chain Network Problem by Three Meta-heuristic Algorithms


  • Developing a three-echelon supply chain network design (SCND) with multi-mode demand satisfaction policy inside of production planning and maintenance
  • Formulating a mixed-integer linear programming model for the problem
  • Using tabu search, harmony search and genetic algorithm to solve the given problem
  • Conducting a Taguchi method to calibrate the parameter of the meta-heuristic algorithms


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