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Hormone Regulation Based Algorithms for Production Scheduling Optimization

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Adaptive Control of Bio-Inspired Manufacturing Systems

Part of the book series: Research on Intelligent Manufacturing ((REINMA))

Abstract

The job-shop scheduling problem is one of the existing combinatorial optimization problems and it has been well known as an NP-hard problem. In order to get a better self-adaptive and stable optimization algorithm, some optimization algorithms inspired from hormone modulation mechanism are proposed and applied to production scheduling problem in this Chapter. Dynamic scheduling problems are also analysed considering the random interference in shop floor scheduling, and the simulation results validate the effectiveness and feasibility.

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Author information

Authors and Affiliations

  1. College of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Dunbing Tang

  2. School of Automotive and Rail Transit, Jiangsu Key Laboratory of Advanced Numerical Control Technology, Nanjing Institute of Technology, Nanjing, China

    Kun Zheng

  3. College of Mechanical and Electrical Engineering, Hohai University, Changzhou, China

    Wenbin Gu

Authors
  1. Dunbing Tang
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  2. Kun Zheng
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  3. Wenbin Gu
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Corresponding author

Correspondence to Dunbing Tang .

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Tang, D., Zheng, K., Gu, W. (2020). Hormone Regulation Based Algorithms for Production Scheduling Optimization. In: Adaptive Control of Bio-Inspired Manufacturing Systems. Research on Intelligent Manufacturing. Springer, Singapore. https://doi.org/10.1007/978-981-15-3445-4_2

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