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A novel bi-vector encoding genetic algorithm for the simultaneous multiple resources scheduling problem

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Abstract

To improve capital effectiveness in light of demand fluctuation, it is increasingly important for high-tech companies to develop effective solutions for managing multiple resources involved in the production. To model and solve the simultaneous multiple resources scheduling problem in general, this study aims to develop a genetic algorithm (bvGA) incorporating with a novel bi-vector encoding method representing the chromosomes of operation sequence and seizing rules for resource assignment in tandem. The proposed model captured the crucial characteristics that the machines were dynamic configuration among multiple resources with limited availability and sequence-dependent setup times of machine configurations between operations would eventually affect performance of a scheduling plan. With the flexibility and computational intelligence that GA empowers, schedule planners can make advanced decisions on integrated machine configuration and job scheduling. According to a number of experiments with simulated data on the basis of a real semiconductor final testing facility, the proposed bvGA has shown practical viability in terms of solution quality as well as computation time.

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Authors and Affiliations

  1. Department of Business Administration, Soochow University, Taipei, Taiwan

    Jei-Zheng Wu

  2. Graduate School of Information, Production and Systems, Waseda University, Kitakyushu-shi, Fukuoka, Japan

    Xin-Chang Hao

  3. Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan

    Chen-Fu Chien

  4. Fuzzy Logic Systems Institute, Fukuoka, Japan

    Mitsuo Gen

Authors
  1. Jei-Zheng Wu
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  2. Xin-Chang Hao
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  3. Chen-Fu Chien
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  4. Mitsuo Gen
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Correspondence to Jei-Zheng Wu.

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Wu, JZ., Hao, XC., Chien, CF. et al. A novel bi-vector encoding genetic algorithm for the simultaneous multiple resources scheduling problem. J Intell Manuf 23, 2255–2270 (2012). https://doi.org/10.1007/s10845-011-0570-0

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  • DOI: https://doi.org/10.1007/s10845-011-0570-0

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