Genetic algorithms for integrated preventive maintenance
planning and production scheduling for a single machine
N. Sortrakul, H.L. Nachtmann, C.R. Cassady
Department of Industrial Engineering, University of Arkansas, 4207 Bell Engineering Center, Fayetteville, AR 72701, USA
Received 3 March 2003; received in revised form 3 November 2003; accepted 28 June 2004
Available online 16 December 2004
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.
# 2004 Elsevier B.V. All rights reserved.
Keywords: Genetic algorithms; Preventive maintenance; Production scheduling; Optimization
Production scheduling and preventive maintenance
(PM) planning are among the most common and
signiﬁcant problems faced by the manufacturing
industry. Production schedules are often interrupted
by equipment failures, which could be prevented by
proper preventive maintenance. However, recom-
mended PM intervals are often delayed in order to
expedite production. Despite the trade-offs between
the two activities, they are typically planned and
executed independently in real manufacturing settings
even if manufacturing productivity can be improved
by optimizing both production scheduling and PM
planning decisions simultaneously.
Numerous studies have been conducted in these
two areas in the past decades. Shapiro  and Pinedo
 reviewed various papers in production scheduling.
Similarly, Sherif and Smith  and Dekker 
reviewed several studies using maintenance optimiza-
tion models. However, almost all relevant studies
considered production scheduling and PM planning as
two independent problems and therefore solve them
Only a few studies have tried to combine and
solve both problems simultaneously. Graves and Lee
 presented a single-machine scheduling problem
with the objective to minimize the total weighted
Computers in Industry 56 (2005) 161–168
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E-mail address: email@example.com (C.R. Cassady).
0166-3615/$ – see front matter # 2004 Elsevier B.V. All rights reserved.