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

Wei Sun, Ying Pan*, Xiaohong Lu and Qinyi Ma
The Journal of Mechanical Science and Technology, vol. 24, no. 10, pp.2119-2125, 2010

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.

Keyword : FJSP; GA; Coding rules; Decoding algorithm

 
 
 
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