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An effective hybrid algorithm for integrated process planning and scheduling

Author

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  • Li, Xinyu
  • Shao, Xinyu
  • Gao, Liang
  • Qian, Weirong

Abstract

Process planning and scheduling are two of the most important functions in the manufacturing system. Traditionally, process planning and scheduling were regarded as separate tasks performed sequentially, where scheduling was implemented after process plans had been generated. However, their functions are usually complementary. If the two systems can be integrated more tightly, greater performance and higher productivity of manufacturing system can be achieved. In this paper, a new hybrid algorithm (HA) based approach has been developed to facilitate the integration and optimization of these two systems. To improve the optimization performance of the approach, an efficient genetic representation, operator and local search strategy have been developed. Experimental studies have been used to test the performance of the proposed approach and to make comparisons between this approach and some previous works. The results show that the research on integrated process planning and scheduling (IPPS) is necessary and the proposed approach is a promising and very effective method on the research of IPPS.

Suggested Citation

  • Li, Xinyu & Shao, Xinyu & Gao, Liang & Qian, Weirong, 2010. "An effective hybrid algorithm for integrated process planning and scheduling," International Journal of Production Economics, Elsevier, vol. 126(2), pages 289-298, August.
    • Handle: RePEc:eee:proeco:v:126:y:2010:i:2:p:289-298
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    References listed on IDEAS

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    1. Thomalla, Christoph S., 2001. "Job shop scheduling with alternative process plans," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 125-134, December.
    2. Eugeniusz Nowicki & Czeslaw Smutnicki, 1996. "A Fast Taboo Search Algorithm for the Job Shop Problem," Management Science, INFORMS, vol. 42(6), pages 797-813, June.
    3. Wahab, M.I.M. & Stoyan, S.J., 2008. "A dynamic approach to measure machine and routing flexibilities of manufacturing systems," International Journal of Production Economics, Elsevier, vol. 113(2), pages 895-913, June.
    4. Anosike, A.I. & Zhang, D.Z., 2009. "An agent-based approach for integrating manufacturing operations," International Journal of Production Economics, Elsevier, vol. 121(2), pages 333-352, October.
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    Citations

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    Cited by:

    1. Ma, Yujie & Du, Gang & Jiao, Roger J., 2020. "Optimal crowdsourcing contracting for reconfigurable process planning in open manufacturing: A bilevel coordinated optimization approach," International Journal of Production Economics, Elsevier, vol. 228(C).
    2. Hyun Cheol Lee & Chunghun Ha, 2019. "Sustainable Integrated Process Planning and Scheduling Optimization Using a Genetic Algorithm with an Integrated Chromosome Representation," Sustainability, MDPI, vol. 11(2), pages 1-23, January.
    3. S. Zhang & T. N. Wong, 2018. "Integrated process planning and scheduling: an enhanced ant colony optimization heuristic with parameter tuning," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 585-601, March.
    4. Zhang, Luping & Wong, T.N., 2015. "An object-coding genetic algorithm for integrated process planning and scheduling," European Journal of Operational Research, Elsevier, vol. 244(2), pages 434-444.
    5. Linda Zhang & Carman K.M. Lee & Pervaiz Akhtar, 2020. "Towards customization: Evaluation of integrated sales, product, and production configuration," Post-Print hal-03276827, HAL.
    6. Xue, Guisen & Felix Offodile, O. & Zhou, Hong & Troutt, Marvin D., 2011. "Integrated production planning with sequence-dependent family setup times," International Journal of Production Economics, Elsevier, vol. 131(2), pages 674-681, June.
    7. Boxuan Zhao & Jianmin Gao & Kun Chen & Ke Guo, 2018. "Two-generation Pareto ant colony algorithm for multi-objective job shop scheduling problem with alternative process plans and unrelated parallel machines," Journal of Intelligent Manufacturing, Springer, vol. 29(1), pages 93-108, January.
    8. Zhang, Linda L. & Lee, Carman K.M. & Akhtar, Pervaiz, 2020. "Towards customization: Evaluation of integrated sales, product, and production configuration," International Journal of Production Economics, Elsevier, vol. 229(C).
    9. Xu Zhang & Zhixue Liao & Lichao Ma & Jin Yao, 2022. "Hierarchical multistrategy genetic algorithm for integrated process planning and scheduling," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 223-246, January.
    10. Barzanji, Ramin & Naderi, Bahman & Begen, Mehmet A., 2020. "Decomposition algorithms for the integrated process planning and scheduling problem," Omega, Elsevier, vol. 93(C).

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