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A hybrid genetic algorithm for production and distribution

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  • Chan, Felix T. S.
  • Chung, S. H.
  • Wadhwa, Subhash

Abstract

This paper develops a hybrid genetic algorithm for production and distribution problems in multi-factory supply chain models. Supply chain problems usually may involve multi-criterion decision-making, for example operating cost, service level, resources utilization, etc. These criteria are numerous and interrelated. To organize them, analytic hierarchy process (AHP) will be utilized. It provides a systematic approach for decision makers to assign weightings and relate them. Meanwhile, genetic algorithms (GAs) will be utilized to determine jobs allocation into suitable production plants. Genetic operators adopted to improve the genetic search algorithm will be introduced and discussed. Finally, a hypothetical production-distribution problem will be solved by the proposed algorithm. The optimization results show that it is reliable and robust.

Suggested Citation

  • Chan, Felix T. S. & Chung, S. H. & Wadhwa, Subhash, 2005. "A hybrid genetic algorithm for production and distribution," Omega, Elsevier, vol. 33(4), pages 345-355, August.
    • Handle: RePEc:eee:jomega:v:33:y:2005:i:4:p:345-355
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    Cited by:

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    9. Kostis Taxakis & Chrissoleon Papadopoulos, 2016. "A design model and a production–distribution and inventory planning model in multi-product supply chain networks," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6436-6457, November.
    10. Ho, William, 2008. "Integrated analytic hierarchy process and its applications - A literature review," European Journal of Operational Research, Elsevier, vol. 186(1), pages 211-228, April.
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    13. Sun, X.T. & Chung, S.H. & Chan, Felix T.S., 2015. "Integrated scheduling of a multi-product multi-factory manufacturing system with maritime transport limits," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 110-127.
    14. Beck, Patrick & Hofmann, Erik, 2012. "Multiple criteria decision making in supply chain management – Currently available methods and possibilities for future research," Die Unternehmung - Swiss Journal of Business Research and Practice, Nomos Verlagsgesellschaft mbH & Co. KG, vol. 66(2), pages 180-213.
    15. Murat İnce & Tuncay Yiğit & Ali Hakan Işik, 2020. "A Novel Hybrid Fuzzy AHP-GA Method for Test Sheet Question Selection," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 629-647, April.
    16. Farahani, Reza Zanjirani & Elahipanah, Mahsa, 2008. "A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain," International Journal of Production Economics, Elsevier, vol. 111(2), pages 229-243, February.
    17. Mohammad Ali Nasiri Khalili & Mostafa Kafaei Razavi & Morteza Kafaee Razavi, 2016. "An Optimized Mathematical Model for Items Supplies Planning of a Logistic System," Modern Applied Science, Canadian Center of Science and Education, vol. 10(10), pages 133-133, October.
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    19. Moo-Sung Sohn & Jiwoong Choi & Hoseog Kang & In-Chan Choi, 2017. "Multiobjective Production Planning at LG Display," Interfaces, INFORMS, vol. 47(4), pages 279-291, August.

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