Title :
The Fuzzy Job-Shop Scheduling Based on Improved Genetic Algorithm
Author :
Liu, Wen-yuan ; Chen, Zhi-Ru ; Shi, Yan ; Yang, Hai-Ying
Author_Institution :
Yan Shan Univ., Qinhuangdao
Abstract :
To improve the performance of the existing genetic algorithms for job shop scheduling problem and speed up searching for optimal scheduling solution, this paper analyzes the difficulty and characteristics of the operation-based coding and designs a new crossover, which is based on the job. As illustrative numerical examples, both 6times6 and 10 times 10 job-shop scheduling problems are considered. Through the comparative simulations with position-based crossover, the feasibility and effectiveness of the proposed crossover are demonstrated.
Keywords :
computer integrated manufacturing; fuzzy set theory; genetic algorithms; integrated manufacturing systems; job shop scheduling; fuzzy job shop scheduling; genetic algorithm; operation-based coding; optimal scheduling solution; position-based crossover; Algorithm design and analysis; Cybernetics; Design engineering; Genetic algorithms; Genetic engineering; Information science; Job shop scheduling; Machine learning; Optimal scheduling; Production; Genetic algorithms; Job crossover; Job-Shop scheduling;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370688
