Modified Adaptive Genetic Algorithms for Solving Job-shop Scheduling Problems

Wan Liang WAN;Qi Di WU;Yi SONG

Systems Engineering - Theory & Practice ›› 2004, Vol. 24 ›› Issue (2) : 58-62.

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PDF(192 KB)
Systems Engineering - Theory & Practice ›› 2004, Vol. 24 ›› Issue (2) : 58-62. DOI: 10.12011/1000-6788(2004)2-58
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Modified Adaptive Genetic Algorithms for Solving Job-shop Scheduling Problems

  • Wan Liang WAN(1),Qi Di WU(2),Yi SONG(1)
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Abstract

Job-shop scheduling problem(JSP) is one of the most difficulty combinatorial optimization problems. It is widely applied to productive management of enterprise. It is one of the most important links on CIMS. This paper proposed improved adaptive genetic algorithms for solving job-shop scheduling problems according to the idea that the best individual on current generation should be kept to next generation, but the best individual should be crossed and mutated by some probability. The software package for th...

Key words

production scheduling / job-shop scheduling genetic algorithms / adaptive / combinatorial optimization

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Wan Liang WAN , Qi Di WU , Yi SONG. Modified Adaptive Genetic Algorithms for Solving Job-shop Scheduling Problems. Systems Engineering - Theory & Practice, 2004, 24(2): 58-62 https://doi.org/10.12011/1000-6788(2004)2-58
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