GENETIC ALGORITHMS WITH A NEW REPAIR OPERATOR FOR ASSEMBLY JOB SHOP SCHEDULING
DOI:
https://doi.org/10.23055/ijietap.2011.18.7.278Keywords:
Process Optimization, Intelligent AlgorithmAbstract
Assembly Job-shop Scheduling Problem (AJSP) starts with JSP and then appends an assembly stage for final product. Assembly constraints decouple is the core technique in genetic algorithms for AJSP. However, repair operators for precedent-infeasible chromosomes in AJSP are less investigated in previous literatures. DSM is used to decouple the assembly constraints by A. Yassine et al. (2007), but it results in more diversity loss of populations. In this paper, a new repair operator (EOBOAFT) is proposed to avoid too much diversity loss after repairing the infeasible chromosomes. Chromosomes map analysis and GA experiments are performed. Results suggest that EOBOAFT always outperforms DSM. An industrial application is given to validate the rationality of this algorithm at last.
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