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Effective heuristics for the dynamic demand joint replenishment problem

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  • E P Robinson

    (Texas A&M University)

  • A Narayanan

    (Texas A&M University)

  • L-L Gao

    (Hofstra University)

Abstract

This paper considers the dynamic demand joint replenishment problem where there is a joint setup cost in each time period when any member of the product family is replenished and a separate setup cost for each different item replenished. We present two forward-pass heuristics, a two-phase heuristic, and a simulated annealing metaheuristic (SAM) and investigate their relative effectiveness in solving a comprehensive set of test problems. The experimental results indicate the two-phase heuristic and the SAM perform better than existing approaches for the problem.

Suggested Citation

  • E P Robinson & A Narayanan & L-L Gao, 2007. "Effective heuristics for the dynamic demand joint replenishment problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(6), pages 808-815, June.
  • Handle: RePEc:pal:jorsoc:v:58:y:2007:i:6:d:10.1057_palgrave.jors.2602197
    DOI: 10.1057/palgrave.jors.2602197
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    References listed on IDEAS

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    1. Awi Federgruen & Michal Tzur, 1994. "The Joint Replenishment Problem with Time-Varying Costs and Demands: Efficient, Asymptotic and ε-Optimal Solutions," Operations Research, INFORMS, vol. 42(6), pages 1067-1086, December.
    2. E. Powell Robinson, Jr. & Li-Lian Gao, 1996. "A Dual Ascent Procedure for Multiproduct Dynamic Demand Coordinated Replenishment with Backlogging," Management Science, INFORMS, vol. 42(11), pages 1556-1564, November.
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    6. Dev Joneja, 1990. "The Joint Replenishment Problem: New Heuristics and Worst Case Performance Bounds," Operations Research, INFORMS, vol. 38(4), pages 711-723, August.
    7. R Y K Fung & X Ma, 2001. "A new method for joint replenishment problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(3), pages 358-362, March.
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    Cited by:

    1. Wang, Lin & He, Jing & Wu, Desheng & Zeng, Yu-Rong, 2012. "A novel differential evolution algorithm for joint replenishment problem under interdependence and its application," International Journal of Production Economics, Elsevier, vol. 135(1), pages 190-198.
    2. He-Yau Kang & Amy H.I. Lee & Chien-Wei Wu & Cheng-Han Lee, 2017. "An efficient method for dynamic-demand joint replenishment problem with multiple suppliers and multiple vehicles," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1065-1084, February.
    3. Narayanan, Arunachalam & Robinson, Powell, 2010. "Efficient and effective heuristics for the coordinated capacitated lot-size problem," European Journal of Operational Research, Elsevier, vol. 203(3), pages 583-592, June.
    4. Pundoor, Guruprasad & Chen, Zhi-Long, 2009. "Joint cyclic production and delivery scheduling in a two-stage supply chain," International Journal of Production Economics, Elsevier, vol. 119(1), pages 55-74, May.
    5. Baller, Annelieke C. & Dabia, Said & Dullaert, Wout E.H. & Vigo, Daniele, 2019. "The Dynamic-Demand Joint Replenishment Problem with Approximated Transportation Costs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1013-1033.
    6. Saravanan Venkatachalam & Arunachalam Narayanan, 2016. "Efficient formulation and heuristics for multi-item single source ordering problem with transportation cost," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4087-4103, July.
    7. Narayanan, Arunachalam & Robinson, Powell, 2010. "Evaluation of joint replenishment lot-sizing procedures in rolling horizon planning systems," International Journal of Production Economics, Elsevier, vol. 127(1), pages 85-94, September.

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