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Genetic Algorithm and Case-Based Reasoning Applied in Production Scheduling

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Knowledge Incorporation in Evolutionary Computation

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 167))

Summary

In this chapter, a case study of hybrid systems with case-based reasoning (CBR) and genetic algorithm for production scheduling is presented. The basics of case-based reasoning and production scheduling will first be presented. A casebased genetic algorithm (CBGA) is then developed to deal with the single machine scheduling problem considering the release time. The objective of case study is to minimize the total weighted completion time. CBGA first retrieves similar cases from the case base, and then incorporates these similar cases into the genetic algorithm to solve new problems at hand. Extensive experimental results showed that CBGA outperformed a few other genetic algorithms in that solutions of better quality can be obtained.

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Author information

Authors and Affiliations

  1. Industrial Engineering and Management Department, Yuan-Ze University, 320, Taiwan, ROC

    Pei-Chann Chang & Yen-Wen Wang

  2. Industrial Management Department, Van-Nung Institute of Technology, 320, Taiwan, ROC

    Jih-Chang Hsieh

Authors
  1. Pei-Chann Chang
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  2. Jih-Chang Hsieh
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  3. Yen-Wen Wang
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Editors and Affiliations

  1. Honda Research Institute Europe GmbH, Carl-Legien-Str.30, D-63073, Offenbach/Main, Germany

    Yaochu Jin

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© 2005 Springer-Verlag Berlin Heidelberg

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Chang, PC., Hsieh, JC., Wang, YW. (2005). Genetic Algorithm and Case-Based Reasoning Applied in Production Scheduling. In: Jin, Y. (eds) Knowledge Incorporation in Evolutionary Computation. Studies in Fuzziness and Soft Computing, vol 167. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44511-1_11

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  • DOI: https://doi.org/10.1007/978-3-540-44511-1_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-06174-5

  • Online ISBN: 978-3-540-44511-1

  • eBook Packages: EngineeringEngineering (R0)

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