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2001 Fiscal Year Final Research Report Summary

Construction method of genetic algorithms for large-scale complex production scheduling problems

Research Project

Project/Area Number 11450154
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field System engineering
Research InstitutionKyoto Institute of Technology

Principal Investigator

SANNOMIYA Nobuo  Kyoto Institute of Technology, Faculty of Engineering and Design, Professor, 工芸学部, 教授 (60026044)

Co-Investigator(Kenkyū-buntansha) IIMA Hitoshi  Kyoto Institute of Technology, Faculty of Engineering and Design, Research Associate, 工芸学部, 助手 (70273547)
Project Period (FY) 1999 – 2001
Keywordsscheduling / job shop process / flowshop process / genetic algorithm / large-scale system / production system / diversity / multi-objective optimization
Research Abstract

1. Proposition of a new selection procedure capable of keeping a diverse population
It was shown that the proposed selection procedure (called Partial Enumeration Selection Method : PESM) can keep a high diversity population through the generations without deteriorating the accuracy of the solution. The robustness of the algorithm was also shown for variations of several schedule parameters.
2. Proposition of decomposition and search space reduction methods
It was shown from computational experiments for large-scale scheduling problems that the proposed decomposition and search space reduction methods work well with genetic algorithms.
3. Design of genetic algorithms capable of dealing flexibly with complex constraints
The design of genetic algorithms was proposed in such a way that the scheduling problems can be solved by only adding a module related to the added constraints. The scheduling problems of a job shop process with parallel machines and the worker allocation problem in a job shop process were solved by the proposed algorithm. Moreover a new decoding method was proposed for no-buffer job shop problems.
4. Application to multi-objective optimization problems
The PESM-based genetic algorithm was applied to solving multi-objective flowshop problems and smooth Pareto fonts were obtained.

  • Research Products

    (12 results)

All Other

All Publications (12 results)

  • [Publications] N.Sannomiya: "Application of Genetic algorithm to a Large-scale Scheduling Problem for a Metal Mold Assembly Process"Proc. of 38th IEEE Conf. on Decision and Control. 2283-2293 (1999)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] C.A.Brizuela: "Controlling Selection Pressure and Diversity in GA's by Partial Enumeration"計測自動制御学会論文集. 36巻4号. 367-369 (2000)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 飯間 等: "大規模フローショップスケジューリング問題に対する分割法を併用した遺伝アルゴリズムの適用"電気学会論文誌C. 121C巻1号. 150-156 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Y.Zhao: "An Improvement of Genetic Algorithms by Search Space Reductions in Solving Large-scale Flowshop Problems"電気学会論文誌C. 121C巻6号. 1010-1015 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] C.A.Brizuela: "Robustness and Diversity in Genetic Algorithms for a Complex Combinatorial Optimization Problem"International Journal of Systems Science. Vol.32 No.9. 1161-1168 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Y.Zhao: "A Genetic Algorithm to Obtain Dead-lock Free Schedules for No-buffer Jobshop Scheduling Problems"計測自動制御学会論文集. 37巻10号. 999-1001 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] N. Sannomiya, H. lima, K. Ashizawa and Y. Kobayashi: "Application of Genetic Algorithm to a Large-scale Scheduling Problem for a Metal Mold Assembly Process"Proc. of 38th IEEE Conf. on Decision and Control. 2288-2293 (1999)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] C. A. Brizuela and N. Sannomiya: "Controlling Selection Pressure and Diversity in GA's by Partial Enumeration"Trans. SICE. Vol.36, No.4. 367-369 (2000)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] H.Iima and N. Sannomiya: "Application of Genetic Algorithm with Decomposition Procedure for a Large Scale Flow Shop Scheduling Problem"Trans. IEE of Japan. Vol. 121-C, No.1. 150-156 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Y. Zhao and N. Sannomiya: "An Improvement of Genetic Algorithms by Search Space Reductions in Solving Large-scale Flowshop Problems"Trans. IEE Of Japan. Vol. 121-C, No.6. 1010-1015 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] C. A. Brizuela and N. Sannomiya: "Robustness and Diversity in Genetic Algorithms for a Complex Combinatorial Optimization Problem"International Journal of Systems Science. Vol. 32, No.9. 1161-1168 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Y. Zhao and N. Sannomiya: "A. Genetic Algorithm to Obtain Dead-lock Free Schedules for No-buffer Jobshop Scheduling Problems"Trans. SICE. Vol. 37, No.10. 999-1001 (2001)

    • Description
      「研究成果報告書概要(欧文)」より

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Published: 2003-09-17  

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