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Research on flexible job-shop scheduling problem based on a modified genetic algorithm

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Abstract

Aiming at the existing problems with GA (genetic algorithm) for solving a flexible job-shop scheduling problem (FJSP), such as description model disunity, complicated coding and decoding methods, a FJSP solution method based on GA is proposed in this paper, and job-shop scheduling problem (JSP) with partial flexibility and JIT (just-in-time) request is transformed into a general FJSP. Moreover, a unified mathematical model is given. Through the improvement of coding rules, decoding algorithm, crossover and mutation operators, the modified GA’s convergence and search efficiency have been enhanced. The example analysis proves the proposed methods can make FJSP converge to the optimal solution steadily, exactly, and efficiently.

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Authors and Affiliations

  1. School of Mechanical Engineering, Dalian University of Technology, Dalian, 116024, China

    Wei Sun, Ying Pan, Xiaohong Lu & Qinyi Ma

  2. Mechanical Engineering Institute, Dalian Fisheries University, Dalian, 116023, China

    Ying Pan

Authors
  1. Wei Sun
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  2. Ying Pan
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  3. Xiaohong Lu
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  4. Qinyi Ma
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Corresponding author

Correspondence to Ying Pan.

Additional information

This paper was recommended for publication in revised form by Associate Editor Kim, Dae-Eun

Wei Sun, born in 1967, is currently a professor and a PhD candidate supervisor in the School of Mechanical and Engineering, Dalian University of Technology, China. His main research interests include production scheduling, CIMS and optimization of complex mechanical equipment, mechanical transmission and structure CAD/CAE, management of product design resource and process.

Ying Pan is currently a PhD candidate in the School of Mechanical and Engineering, Dalian University of Technology, China. Meanwhile, she serves as a lecturer in Mechanical Engineering Institute, Dalian Fisheries University, China. Her research interests include production scheduling, production engineering, manufacturing execution system and multi-agent system.

X iaohong Lu is currently a postdoctoral in the School of Mechanical and Engineering, Dalian University of Technology, China. Her main research interests include production scheduling, CIMS, production engineering, mechanical transmission and structure CAD/CAE, management of product design resource and process.

Qinyi Ma is currently a PhD candidate in School of Mechanical and Engineering, Dalian University of Technology, China. Her research interests focus on knowledge-based product digital design.

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Sun, W., Pan, Y., Lu, X. et al. Research on flexible job-shop scheduling problem based on a modified genetic algorithm. J Mech Sci Technol 24, 2119–2125 (2010). https://doi.org/10.1007/s12206-010-0526-x

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  • DOI: https://doi.org/10.1007/s12206-010-0526-x

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