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A novel genetic algorithm for the maximum coverage problem in the three-level supply chain network

Author

Listed:
  • Omid Rahmani
  • Bahman Naderi
  • Mohammad Mohammadi
  • Mehrdad Nouri Koupaei

Abstract

The maximum coverage problem is one of the most functional location issues. Nowadays, organisations are seeking to increase profits and one of the competitive advantages for organisations is efficient and effective designing of supply chain network. On the other hand, given the importance of distribution planning among the levels of supply chain, vehicle routing problem needs to be explored which leads to a significant reduction in costs of supply chain network. The purpose of this research is designing a supply chain network that includes the supply, distribution centres and retailers. It should be noted that the coverage radius is defined for all distribution centres and distribution centres gives any services to retailers that is within the actual coverage. Also, this service is done on routing. Since that the classical vehicle routing problem is NP-hard, to solve the problem in small and medium sizes, we used the GAMS software. Next, genetic algorithms and simulated annealing is used to solve the problem in large size. Finally, the results have been evaluated.

Suggested Citation

  • Omid Rahmani & Bahman Naderi & Mohammad Mohammadi & Mehrdad Nouri Koupaei, 2018. "A novel genetic algorithm for the maximum coverage problem in the three-level supply chain network," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 30(2), pages 219-236.
    • Handle: RePEc:ids:ijisen:v:30:y:2018:i:2:p:219-236
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