NDLI: Application on job-shop scheduling with Genetic Algorithm based on the mixed strategy

Content Provider	IEEE Xplore Digital Library
Author	Liang Xu Wang Shuang Huang Ming
Copyright Year	2009
Description	Author affiliation: Software Technology Institute, Dalian Jiao Tong University, 116028, China (Liang Xu; Wang Shuang; Huang Ming)
Abstract	Adaptive Genetic Algorithm for solving job-shop scheduling problems has the defects of the slow convergence speed on the early stage and it is easy to trap into local optimal solutions, this paper introduces a time operator depending on the time evolution to solve this problem. Its purpose is to overcome the defect of adaptive Genetic Algorithm whose crossover and mutation probability can not make a corresponding adjustment with evolutionary process. Algorithm's structure is hierarchical, scheduling problems can be fully demonstrated the characteristics by using this strategy, not only improve the convergence rate but also maintain the diversity of the population, furthermore avoid premature. The population in the same layer evolve with two goals-time optimal and cost optimal at the same time, the basic Genetic Algorithm is applied between layers. The improved algorithm was tested by Muth and Thompson benchmarks, the results show that the optimized algorithm is highly efficient and improves both the quality of solutions and speed of convergence.
Starting Page	2007
Ending Page	2009
File Size	249186
Page Count	3
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5191650
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Adaptive Genetic mutations Benchmark testing Cost function Time operator Application software Hierarchic structure Scheduling algorithm Genetic algorithms Convergence Design optimization
Content Type	Text
Resource Type	Article

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