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Application of genetic approach for advanced planning in multi-factory environment

Author

Listed:
  • Chung, S.H.
  • Lau, H.C.W.
  • Choy, K.L.
  • Ho, G.T.S.
  • Tse, Y.K.

Abstract

This paper deals with multi-factory production scheduling problems which consist of a number of factories. Each factory consists of various machines and is capable of performing various operations. Some factories may produce intermediate products and supply to other factories for assembly purpose, while some factories may produce finished products and supply to end customers. The model is subject to capacity constraints, precedence relationship, and alternative machining with different processing time. The problem encountered is to determine how to cope with each factory and machine in the system, and the objective is to minimize the makespan of a set of given jobs through proper collaboration. The makespan takes into account the processing time, transportation time between resources, and machine set-up time. This paper proposes a modified genetic algorithm to deal with the problem. The optimization reliability of the proposed algorithm has been tested by comparing it with existing approaches and simple genetic algorithms in several numerical examples found in literatures. The influence of different crossover and mutation rates on the performance of genetic search in simple genetic algorithms has also been demonstrated. The results also show the robustness of the proposed algorithm in this problem.

Suggested Citation

  • Chung, S.H. & Lau, H.C.W. & Choy, K.L. & Ho, G.T.S. & Tse, Y.K., 2010. "Application of genetic approach for advanced planning in multi-factory environment," International Journal of Production Economics, Elsevier, vol. 127(2), pages 300-308, October.
    • Handle: RePEc:eee:proeco:v:127:y:2010:i:2:p:300-308
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    References listed on IDEAS

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    1. Gnoni, M. G. & Iavagnilio, R. & Mossa, G. & Mummolo, G. & Di Leva, A., 2003. "Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry," International Journal of Production Economics, Elsevier, vol. 85(2), pages 251-262, August.
    2. Christodoulos Floudas & Xiaoxia Lin, 2005. "Mixed Integer Linear Programming in Process Scheduling: Modeling, Algorithms, and Applications," Annals of Operations Research, Springer, vol. 139(1), pages 131-162, October.
    3. Thomas, Douglas J. & Griffin, Paul M., 1996. "Coordinated supply chain management," European Journal of Operational Research, Elsevier, vol. 94(1), pages 1-15, October.
    4. Guinet, Alain, 2001. "Multi-site planning: A transshipment problem," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 21-32, December.
    5. Vercellis, Carlo, 1999. "Multi-plant production planning in capacitated self-configuring two-stage serial systems," European Journal of Operational Research, Elsevier, vol. 119(2), pages 451-460, December.
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    Cited by:

    1. Ali Gharaei & Fariborz Jolai, 2021. "A Pareto approach for the multi-factory supply chain scheduling and distribution problem," Operational Research, Springer, vol. 21(4), pages 2333-2364, December.
    2. 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.
    3. Seyed Ahmad Razavi Al-e-hashem & Ali Papi & Mir Saman Pishvaee & Mohammadreza Rasouli, 2022. "Robust maintenance planning and scheduling for multi-factory production networks considering disruption cost: a bi-objective optimization model and a metaheuristic solution method," Operational Research, Springer, vol. 22(5), pages 4999-5034, November.
    4. J. Behnamian & S. M. T. Fatemi Ghomi, 2016. "A survey of multi-factory scheduling," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 231-249, February.
    5. Linda Zhang & Carman Lee & Shuzhu Zhang, 2016. "An integrated model for strategic supply chain design: Formulation and ABC-based solution approach," Post-Print hal-01744868, HAL.
    6. Jafar-Zanjani, Hamed & Zandieh, Mostafa & Sharifi, Mani, 2022. "Robust and resilient joint periodic maintenance planning and scheduling in a multi-factory network under uncertainty: A case study," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    7. Ławrynowicz Anna, 2011. "Genetic Algorithms for Solving Scheduling Problems in Manufacturing Systems," Foundations of Management, Sciendo, vol. 3(2), pages 7-26, January.

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