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Combining Extended Imperialist Competitive Algorithm with a Genetic Algorithm to Solve the Distributed Integration of Process Planning and Scheduling Problem

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  • Shuai Zhang
  • Yangbing Xu
  • Zhinan Yu
  • Wenyu Zhang
  • Dejian Yu

Abstract

Distributed integration of process planning and scheduling (DIPPS) extends traditional integrated process planning and scheduling (IPPS) by considering the distributed features of manufacturing. In this study, we first establish a mathematical model which contains all constraints for the DIPPS problem. Then, the imperialist competitive algorithm (ICA) is extended to effectively solve the DIPPS problem by improving country structure, assimilation strategy, and adding resistance procedure. Next, the genetic algorithm (GA) is adapted to maintain the robustness of the plan and schedule after machine breakdown. Finally, we perform a two-stage experiment to prove the effectiveness and efficiency of extended ICA and GA in solving DIPPS problem with machine breakdown.

Suggested Citation

  • Shuai Zhang & Yangbing Xu & Zhinan Yu & Wenyu Zhang & Dejian Yu, 2017. "Combining Extended Imperialist Competitive Algorithm with a Genetic Algorithm to Solve the Distributed Integration of Process Planning and Scheduling Problem," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-13, November.
    • Handle: RePEc:hin:jnlmpe:9628935
    DOI: 10.1155/2017/9628935
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