Genetic algorithms for integrated preventive maintenance planning and production scheduling for a single machine

Authors:
N. Sortrakul;H. L. Nachtmann;C. R. Cassady
Affiliations:
Department of Industrial Engineering, University of Arkansas 4207 Bell Engineering Center, Fayetteville, AR;Department of Industrial Engineering, University of Arkansas 4207 Bell Engineering Center, Fayetteville, AR;Department of Industrial Engineering, University of Arkansas 4207 Bell Engineering Center, Fayetteville, AR
Venue:
Computers in Industry - Special issue: Application of genetics algorithms in industry
Year:
2005

Citing 5
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Abstract

Despite the inter-dependent relationship between them, production scheduling and preventive maintenance planning decisions are generally analyzed and executed independently in real manufacturing systems. This practice is also found in the majority of the studies found in the relevant literature. In this paper, heuristics based on genetic algorithms are developed to solve an integrated optimization model for production scheduling and preventive maintenance planning. The numerical results on several problem sizes indicate that the proposed genetic algorithms are very efficient for optimizing the integrated problem.