Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 49, Issue 13, Pages 3891-3918Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2010.492405
Keywords
scheduling; job shop; maintenance; multi-objective genetic algorithms; lower bounds; GA parameters
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This paper deals with the job shop problem of simultaneous scheduling of production operations and preventive maintenance tasks. To solve this problem, we develop an elitist multi-objective genetic algorithm that provides a set of Pareto optimal solutions minimising the makespan and the total maintenance cost. A deep study was made to choose the best encoding, operators, and the different probabilities. Some lower bounds of the adopted criteria are developed. The computational experiments carried out on a set of published instances validate the efficiency of the proposed algorithm.
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