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An Artificial Immune Algorithm for a Closed-Loop Supply Chain Network Design Problem with Different Delivery Paths

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  • Ehsan Yadegari

    (Department of Industrial Management, Shahid Beheshti University, Tehran, Iran)

  • Mostafa Ekhtiari

    (Department of Industrial Management, Shahid Beheshti University, Tehran, Iran)

  • Mostafa Zandieh

    (Department of Industrial Management, Shahid Beheshti University, Tehran, Iran)

  • Akbar Alem-Tabriz

    (Department of Industrial Management, Shahid Beheshti University, Tehran, Iran)

Abstract

The concern about customer satisfaction and transportation cost in the business environment has spurred an interest in designing a flexible logistics network. This paper proposes a multi-delivery path closed-loop supply chain network to find not only the most cost efficient network design but also the best path to deliver the products to customers. To tackle with such an NP-hard problem an Artificial Immune Algorithm (AIA) is modified. To show the efficiency and accuracy of the proposed method numerical experiments are conducted. Consequently, the computational results validate the quality of the proposed approach by comparing them with those of obtained with exact methods.

Suggested Citation

  • Ehsan Yadegari & Mostafa Ekhtiari & Mostafa Zandieh & Akbar Alem-Tabriz, 2014. "An Artificial Immune Algorithm for a Closed-Loop Supply Chain Network Design Problem with Different Delivery Paths," International Journal of Strategic Decision Sciences (IJSDS), IGI Global, vol. 5(3), pages 27-46, July.
    • Handle: RePEc:igg:jsds00:v:5:y:2014:i:3:p:27-46
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    Cited by:

    1. Elham Behmanesh & Jürgen Pannek, 2021. "A Comparison between Memetic Algorithm and Genetic Algorithm for an Integrated Logistics Network with Flexible Delivery Path," SN Operations Research Forum, Springer, vol. 2(3), pages 1-24, September.

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