Maintenance Optimization using Combined Fuzzy Genetic Algorithm and Local Search

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• 作者：I Maatouk^* ; ^{imane.maatouk@yahoo.com" class="auth_mail" title="E-mail the corresponding author} ; N. Chebbo^* ; ^{nchebbo@ul.edu.lb" class="auth_mail" title="E-mail the corresponding author} ; I. Jarkass^* ; ^{ijarhass@ul.edu.lb" class="auth_mail" title="E-mail the corresponding author} ; E. Chatelet^** ; ^{eric.chatelet@utt.fr" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Fuzzy logic ; genetic algorithm ; local search ; optimization ; preventive maintenance
• 刊名：IFAC-PapersOnLine
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：49
• 期：12
• 页码：757-762
• 全文大小：520 K

文摘

This paper presents an hybridization fuzzy logic controlled genetic algorithm, and local search to solve the preventive maintenance optimization problem in a multi-states series-parallel system. The objective is to optimize for each system component the maintenance policy minimizing a cost function under the constraint of required availability and for a specified period. Simulation results are presented for the proposed method which is compared to a genetic algorithm with fixed crossover and mutation probabilities, and to a fuzzy logic controlled genetic algorithm. The experimental results show the advantages and the efficiency of the hybridization FLC-GA, and local search.