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Ant Colony Algorithm And Multi-Agent-Based Production Scheduling Optimization Model

Author

Listed:
  • Jinghua zhao

    (School of Management, University of Shanghai for Science and Technology,200093,China)

  • Jie Lin

    (School of Economics and Management, Tongji University, 200092 Shanghai, China)

  • Xia Zhao

    (Department of Information Systems and Operations Management, University of North Carolina at Greensboro, Greensboro, NC 27402, USA)

Abstract

In the dynamic production environment of supply chain, based on information sharing among enterprises of supply chain, this paper puts forward a production scheduling optimization model for supply chain. It transforms the choice of cooperative enterprises and their process ordering into the choice of path in graph theory. With respect to the complexity of model solving, this paper designs an expert system aided multi-agent intelligent ant colony algorithm to solve the production scheduling optimization model， where ant colony is constructed with multi-agent and the order decomposition structure and constraint are expressed by expert system. Also, supply chain production scheduling optimization prototype architecture is implemented and the related technologies are given in the paper. Finally using the system，several experiments are conducted，which show that both of the model and the algorithm are effective and feasible.

Suggested Citation

  • Jinghua zhao & Jie Lin & Xia Zhao, 2017. "Ant Colony Algorithm And Multi-Agent-Based Production Scheduling Optimization Model," Malaysian E Commerce Journal (MECJ), Zibeline International Publishing, vol. 1(1), pages 1-6, January.
    • Handle: RePEc:zib:zbmecj:v:1:y:2017:i:1:p:1-6
    DOI: 10.26480/mecj.01.2017.01.06
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    References listed on IDEAS

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    1. Hung, Wing Yan & Samsatli, Nouri J. & Shah, Nilay, 2006. "Object-oriented dynamic supply-chain modelling incorporated with production scheduling," European Journal of Operational Research, Elsevier, vol. 169(3), pages 1064-1076, March.
    2. Mula, Josefa & Peidro, David & Díaz-Madroñero, Manuel & Vicens, Eduardo, 2010. "Mathematical programming models for supply chain production and transport planning," European Journal of Operational Research, Elsevier, vol. 204(3), pages 377-390, August.
    3. Stephan Kreipl & Jörg Dickersbach, 2008. "Scheduling coordination problems in supply chain planning," Annals of Operations Research, Springer, vol. 161(1), pages 103-122, July.
    4. P Tormos & A Lova, 2001. "Tools for resource-constrained project scheduling and control: forward and backward slack analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(7), pages 779-788, July.
    5. Lodree, Emmett Jr., 2007. "Advanced supply chain planning with mixtures of backorders, lost sales, and lost contract," European Journal of Operational Research, Elsevier, vol. 181(1), pages 168-183, August.
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