Abstract
We propose in this article an evolutionary algorithm for the problem of scheduling N production jobs on M parallel machines. Each machine should be blocked once during the planning horizon for reasons of preventive maintenance. In our study, the maintenance tasks should continuously be performed because the maintenance resources are not sufficient. We aim to find a schedule composed of the production jobs and the maintenance tasks with a minimal preventive maintenance cost and total sum of production job’s weighted completion times.
Computational experiments are performed on randomly generated instances. The results show that the evolutionary algorithm is able to produce appropriate solutions for the problem.
Keywords
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aghezzaf, E.H., Jamali, M.A., Ait-Kadi, D.: An integrated production and preventive maintenance planning model. European Journal of Operational Research 181, 679–685 (2007)
Aghezzaf, E.H., Najid, N.M.: Integrated production planning and preventive maintenance in deteriorating production systems. Information Sciences 178, 3382–3392 (2008)
Eastman, W.L., Even, S., Isaacs, I.M.: Bounds for optimal scheduling of n jobs on m processors. Management science 11, 268–279 (1964)
Mellouli, R., Cherif, S., Chou, C., Kacem, I.: Identical parallel-machine scheduling under availability constraints to minimize the sum of completion times. European Journal of Operational Research 197, 1150–1167 (2009)
Graves, H.G., Lee, C.-Y.: Scheduling Maintenance and Semiresumable Jobs on a Single Machine. Naval Research Logistics 46, 845–863 (1999)
Kacem, I., Chu, C., Souissi, A.: Single-machine scheduling with an availability constraint to minimize the weighted sum of the completion times. Computers & Operations Research 35, 827–844 (2008)
Kubiak, W., Blazewicz, J., Formanowicz, P., Breit, J., Schmidt, G.: Two-machine flow shops with limited machine availability. European Journal of Operational Research 136, 528–540 (2002)
Lee, C.-Y.: Minimising the makespan in the two machine scheduling scheduling problem with an availability constraint. Operational Research Letters 20, 129–139 (2000)
Lee, C.-Y., Chen, Z.-L.: Scheduling Jobs and Maintenance Activities on Parallel Machines. Naval Research Logistics 47, 145–165 (2000)
Li, G.: Single machine earliness and tardiness scheduling. European Journal of Operational Research 26, 546–558 (1997)
Liaw, C.-F.: A branch and bound algorithm for the single machine earliness and tardiness scheduling problem. Computers & Operations Research 26, 679–693 (1999)
Potts, C.N., van Wassenhove, L.N.: A Branch and Bound Algorithm for the Total Weighted Tardiness Problem. Operations Research 33(2), 363–377 (1985)
Rebai, M., Kacem, I., Adjallah, K.H.: Earliness tardiness minimization on a single machine to schedule preventive maintenance tasks: metaheuristic and exact methods. Journal of Intelligent Manufacturing (2010), doi:10.1007/s10845-010-0425-0
Rebai, M.: Ordonnancement des taches de production et de maintenance preventive sur machines paralleles. PhD Thesis of Troyes University of Technology 2011, Troyes, France July 1 (2011)
Sourd, F., Keded-Sidhoum, S., Rio Solis, Y.: Lower bounds for the earliness-tardiness scheduling problem on parallel machines with distinct due dates. European Journal of Operational Research 189, 1305–1319 (2008)
Smith, W.E.: Various optimizers for single-stage production. Naval Research Logistics Quarterly 3, 59–66 (1956)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rebai, M., Kacem, I., Adjallah, K.H. (2012). Evolutionary Algorithm for Scheduling Production Jobs and Preventive Maintenance Activities. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds) Business Process Management Workshops. BPM 2011. Lecture Notes in Business Information Processing, vol 100. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28115-0_15
Download citation
DOI: https://doi.org/10.1007/978-3-642-28115-0_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28114-3
Online ISBN: 978-3-642-28115-0
eBook Packages: Computer ScienceComputer Science (R0)