Research on Parallel Hybrid Genetic Algorithm Based on Multi-Group in Job Shop Scheduling

Cun Liang Yan; Wei Feng Shi; Rui Lin Zhao

doi:10.4028/www.scientific.net/AMR.482-484.2227

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 482-484Research on Parallel Hybrid Genetic Algorithm...

Research on Parallel Hybrid Genetic Algorithm Based on Multi-Group in Job Shop Scheduling

Abstract:

To avoid premature and sensitivity of operator parameters selecting of Standard genetic algorithm (SGA) and simulated annealing genetic algorithm (SAGA), a parallel hybrid genetic algorithm based on multi-group (hybrid GA) is presented. The algorithm combines the ideas of parallel computation, simulated annealing and genetic algorithm, and uses orthogonal test table selecting operator parameters to improve the efficiency and robust of the algorithm. And benchmark example of job shop scheduling problem (JSP) is used to validate the effectiveness of the algorithm. Results show the hybrid genetic algorithm converges quickly with small impact to operator parameters.

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Periodical:

Advanced Materials Research (Volumes 482-484)

Pages:

2227-2233

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.482-484.2227

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Online since:

February 2012

Authors:

Cun Liang Yan, Wei Feng Shi, Rui Lin Zhao

Keywords:

Genetic Algorithm (GA), Job Shop Scheduling, Orthogonal Test, Simulated Annealing Genetic Algorithm

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References

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