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Changeover formulations for discrete-time mixed-integer programming scheduling models

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  • Velez, Sara
  • Dong, Yachao
  • Maravelias, Christos T.

Abstract

Changeover times can have a significant impact on the scheduling of manufacturing operations. Unfortunately, accounting for changeovers in mixed-integer programming (MIP) scheduling formulations makes the resulting models computationally more expensive. We propose five new formulations for sequence-dependent changeovers, applicable to a wide range of scheduling problems. We generate constraints for different sets of time points and sets of tasks. We also propose valid inequalities for makespan minimization. Furthermore, we prove results regarding the relative tightness of each formulation. Finally, we perform a computational study. Interestingly, we find that tighter formulations do not always lead to faster solution times, and we show that some of the new formulations perform better than the previously proposed ones.

Suggested Citation

  • Velez, Sara & Dong, Yachao & Maravelias, Christos T., 2017. "Changeover formulations for discrete-time mixed-integer programming scheduling models," European Journal of Operational Research, Elsevier, vol. 260(3), pages 949-963.
    • Handle: RePEc:eee:ejores:v:260:y:2017:i:3:p:949-963
    DOI: 10.1016/j.ejor.2017.01.004
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    1. Baptiste, Philippe & Peridy, Laurent & Pinson, Eric, 2003. "A branch and bound to minimize the number of late jobs on a single machine with release time constraints," European Journal of Operational Research, Elsevier, vol. 144(1), pages 1-11, January.
    2. Ruslan Sadykov & Laurence A. Wolsey, 2006. "Integer Programming and Constraint Programming in Solving a Multimachine Assignment Scheduling Problem with Deadlines and Release Dates," INFORMS Journal on Computing, INFORMS, vol. 18(2), pages 209-217, May.
    3. J.M. van den Akker & C.A.J. Hurkens & M.W.P. Savelsbergh, 2000. "Time-Indexed Formulations for Machine Scheduling Problems: Column Generation," INFORMS Journal on Computing, INFORMS, vol. 12(2), pages 111-124, May.
    4. Vipul Jain & Ignacio E. Grossmann, 2001. "Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 13(4), pages 258-276, November.
    5. Christian Artigues & Dominique Feillet, 2008. "A branch and bound method for the job-shop problem with sequence-dependent setup times," Annals of Operations Research, Springer, vol. 159(1), pages 135-159, March.
    6. Uday S. Karmarkar & Linus Schrage, 1985. "The Deterministic Dynamic Product Cycling Problem," Operations Research, INFORMS, vol. 33(2), pages 326-345, April.
    7. Kopanos, Georgios M. & Méndez, Carlos A. & Puigjaner, Luis, 2010. "MIP-based decomposition strategies for large-scale scheduling problems in multiproduct multistage batch plants: A benchmark scheduling problem of the pharmaceutical industry," European Journal of Operational Research, Elsevier, vol. 207(2), pages 644-655, December.
    8. J. N. Hooker, 2007. "Planning and Scheduling by Logic-Based Benders Decomposition," Operations Research, INFORMS, vol. 55(3), pages 588-602, June.
    9. Danielle Zyngier & Jeffrey D. Kelly, 2009. "Multi-Product Inventory Logistics Modeling in the Process Industries," Springer Optimization and Its Applications, in: Wanpracha Chaovalitwongse & Kevin C. Furman & Panos M. Pardalos (ed.), Optimization and Logistics Challenges in the Enterprise, pages 61-95, Springer.
    10. John N. Hooker, 2007. "Integrated Methods for Optimization," International Series in Operations Research and Management Science, Springer, number 978-0-387-38274-6, December.
    11. Elvin Coban & J. Hooker, 2013. "Single-facility scheduling by logic-based Benders decomposition," Annals of Operations Research, Springer, vol. 210(1), pages 245-272, November.
    12. Wolsey, Laurence A., 1997. "MIP modelling of changeovers in production planning and scheduling problems," European Journal of Operational Research, Elsevier, vol. 99(1), pages 154-165, May.
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    Cited by:

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    2. Hao, Jun & Li, Jianping & Wu, Dengsheng & Sun, Xiaolei, 2020. "Portfolio optimisation of material purchase considering supply risk – A multi-objective programming model," International Journal of Production Economics, Elsevier, vol. 230(C).
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    4. Kramer, Arthur & Iori, Manuel & Lacomme, Philippe, 2021. "Mathematical formulations for scheduling jobs on identical parallel machines with family setup times and total weighted completion time minimization," European Journal of Operational Research, Elsevier, vol. 289(3), pages 825-840.

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