Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems
 PeiChann Chang,
 ShihHsin Chen,
 ChinYuan Fan,
 V. Mani
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In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the “evaporation concept” applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The “evaporation concept” is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.
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 Title
 Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems
 Journal

Annals of Operations Research
Volume 180, Issue 1 , pp 197211
 Cover Date
 20101101
 DOI
 10.1007/s1047900804899
 Print ISSN
 02545330
 Online ISSN
 15729338
 Publisher
 Springer US
 Additional Links
 Topics
 Keywords

 Evolutionary algorithm with probabilistic models
 Single machine scheduling
 Total deviations
 Flowshop machine scheduling
 Artificial chromosomes
 Industry Sectors
 Authors

 PeiChann Chang ^{(1)}
 ShihHsin Chen ^{(2)}
 ChinYuan Fan ^{(3)}
 V. Mani ^{(4)}
 Author Affiliations

 1. Department of Information Management, YuanZe University, 135 Yuan Tung Road, ChungLi, Taiwan, ROC, 32026
 2. Department of Electronic Commerce Management, Nanhua University, 32, Chungkeng, Dalin, Chiayi, 62248, Taiwan, ROC
 3. Department of Industrial Engineering and Management, YuanZe University, ChungLi, Taiwan, ROC
 4. Department of Aerospace Engineering, Indian Institute of Science, Bangalore, India