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An Enhanced Migrating Birds Optimization for the Flexible Job Shop Scheduling Problem with Lot Streaming

  • Tao Meng
  • Quan-ke Pan
  • Qing-da Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10954)

Abstract

This paper presents an enhanced migrating birds optimization (enMBO) for the flexible job shop scheduling problem with the consideration of lot streaming and the goal is minimizing total flowtime. In enMBO, to explore the solution space efficiently, we design a search scheme which is capable of adjusting the search radius with the increase of iteration. In addition, MBO concentrates too much on local search and hence is easily trapped in local optimum. To handle this, a special mechanism that based on precedence operation crossover is developed and incorporated into the evolutionary framework. We conduct simulations on well-known benchmarks with different scales and results verify the significance of schemes designed above. Moreover, by comparing with recent algorithms, the proposed enMBO shows its high performance for the considered problem.

Keywords

Flexible job shop scheduling problem Migrating birds optimization Lot streaming Crossover operation Meta-heuristic 

Notes

Acknowledgments

This research is partially supported by the National Science Foundation of China 51575212 and 61174187, and Shanghai Key Laboratory of Power station Automation Technology.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mechatronic Engineering and AutomationShanghai UniversityShanghaiPeople’s Republic of China
  2. 2.School of Mathematical ScienceLiaocheng UniversityLiaochengPeople’s Republic of China
  3. 3.State Key Laboratory of Synthetic Automation for Process IndustriesNortheastern UniversityShenyangPeople’s Republic of China

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