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Lagrangean relaxation based heuristics for lot sizing with setup times

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  • Süral, Haldun
  • Denizel, Meltem
  • Van Wassenhove, Luk N.

Abstract

We consider a lot sizing problem with setup times where the objective is to minimize the total inventory carrying cost only. The demand is dynamic over time and there is a single resource of limited capacity. We show that the approaches implemented in the literature for more general versions of the problem do not perform well in this case. We examine the Lagrangean relaxation (LR) of demand constraints in a strong reformulation of the problem. We then design a primal heuristic to generate upper bounds and combine it with the LR problem within a subgradient optimization procedure. We also develop a simple branch and bound heuristic to solve the problem. Computational results on test problems taken from the literature show that our relaxation procedure produces consistently better solutions than the previously developed heuristics in the literature.

Suggested Citation

  • Süral, Haldun & Denizel, Meltem & Van Wassenhove, Luk N., 2009. "Lagrangean relaxation based heuristics for lot sizing with setup times," European Journal of Operational Research, Elsevier, vol. 194(1), pages 51-63, April.
    • Handle: RePEc:eee:ejores:v:194:y:2009:i:1:p:51-63
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    2. Silvio Alexandre de Araujo & Bert De Reyck & Zeger Degraeve & Ioannis Fragkos & Raf Jans, 2015. "Period Decompositions for the Capacitated Lot Sizing Problem with Setup Times," INFORMS Journal on Computing, INFORMS, vol. 27(3), pages 431-448, August.
    3. Melega, Gislaine Mara & de Araujo, Silvio Alexandre & Jans, Raf, 2018. "Classification and literature review of integrated lot-sizing and cutting stock problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 1-19.
    4. Kerem Akartunalı & Ioannis Fragkos & Andrew J. Miller & Tao Wu, 2016. "Local Cuts and Two-Period Convex Hull Closures for Big-Bucket Lot-Sizing Problems," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 766-780, November.
    5. Neves-Moreira, Fábio & Almada-Lobo, Bernardo & Cordeau, Jean-François & Guimarães, Luís & Jans, Raf, 2019. "Solving a large multi-product production-routing problem with delivery time windows," Omega, Elsevier, vol. 86(C), pages 154-172.
    6. Tao Wu, 2022. "Predictive Search for Capacitated Multi-Item Lot Sizing Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 385-406, January.
    7. Cunha, Artur Lovato & Santos, Maristela Oliveira & Morabito, Reinaldo & Barbosa-Póvoa, Ana, 2018. "An integrated approach for production lot sizing and raw material purchasing," European Journal of Operational Research, Elsevier, vol. 269(3), pages 923-938.
    8. Zhang, Zhi-Hai & Jiang, Hai & Pan, Xunzhang, 2012. "A Lagrangian relaxation based approach for the capacitated lot sizing problem in closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 140(1), pages 249-255.
    9. Muller, Laurent Flindt & Spoorendonk, Simon & Pisinger, David, 2012. "A hybrid adaptive large neighborhood search heuristic for lot-sizing with setup times," European Journal of Operational Research, Elsevier, vol. 218(3), pages 614-623.
    10. Dziuba, Daryna & Almeder, Christian, 2023. "New construction heuristic for capacitated lot sizing problems," European Journal of Operational Research, Elsevier, vol. 311(3), pages 906-920.
    11. Ioannis Fragkos & Zeger Degraeve & Bert De Reyck, 2016. "A Horizon Decomposition Approach for the Capacitated Lot-Sizing Problem with Setup Times," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 465-482, August.
    12. Taş, Duygu & Gendreau, Michel & Jabali, Ola & Jans, Raf, 2019. "A capacitated lot sizing problem with stochastic setup times and overtime," European Journal of Operational Research, Elsevier, vol. 273(1), pages 146-159.
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