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Worst case analysis for a general class of on-line lot-sizing heuristics

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  • van den Heuvel, W.
  • Wagelmans, A.P.M.

Abstract

In this paper we analyze the worst case performance of heuristics for the classical economic lot-sizing problem with time-invariant cost parameters. We consider a general class of on-line heuristics that is often applied in a rolling horizon environment. We develop a procedure to systematically construct worst case instances for a fixed time horizon and use it to derive worst case problem instances for an infinite time horizon. Our analysis shows that any on-line heuristic has a worst case ratio of at least 2. Furthermore, we show how the results can be used to construct heuristics with optimal worst case performance for small model horizons.

Suggested Citation

  • van den Heuvel, W. & Wagelmans, A.P.M., 2007. "Worst case analysis for a general class of on-line lot-sizing heuristics," Econometric Institute Research Papers EI 2007-46, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:10859
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    1. Stadtler, Hartmut, 2000. "Improved rolling schedules for the dynamic single level lot sizing problem," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 14079, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
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    Cited by:

    1. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 0. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    2. Adam N. Elmachtoub & Retsef Levi, 2016. "Supply Chain Management with Online Customer Selection," Operations Research, INFORMS, vol. 64(2), pages 458-473, April.
    3. Absi, Nabil & van den Heuvel, Wilco, 2019. "Worst case analysis of Relax and Fix heuristics for lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 279(2), pages 449-458.
    4. J. Brinkhuis, 2009. "Convex Duality and Calculus: Reduction to Cones," Journal of Optimization Theory and Applications, Springer, vol. 143(3), pages 439-453, December.
    5. Brahimi, Nadjib & Absi, Nabil & Dauzère-Pérès, Stéphane & Nordli, Atle, 2017. "Single-item dynamic lot-sizing problems: An updated survey," European Journal of Operational Research, Elsevier, vol. 263(3), pages 838-863.
    6. Niv Buchbinder & Tracy Kimbrel & Retsef Levi & Konstantin Makarychev & Maxim Sviridenko, 2013. "Online Make-to-Order Joint Replenishment Model: Primal-Dual Competitive Algorithms," Operations Research, INFORMS, vol. 61(4), pages 1014-1029, August.
    7. Massonnet, G. & Gayon, J.-P. & Rapine, C., 2014. "Approximation algorithms for deterministic continuous-review inventory lot-sizing problems with time-varying demand," European Journal of Operational Research, Elsevier, vol. 234(3), pages 641-649.
    8. van den Heuvel, W.J. & Wagelmans, A.P.M., 2008. "A holding cost bound for the economic lot-sizing problem with time-invariant cost parameters," Econometric Institute Research Papers EI 2008-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Guanqun Ni, 2023. "An improved online replenishment policy and its competitive ratio analysis for a purchase-to-order seller," Journal of Combinatorial Optimization, Springer, vol. 46(2), pages 1-14, September.
    10. Adam N. Elmachtoub & Retsef Levi, 2015. "From Cost Sharing Mechanisms to Online Selection Problems," Mathematics of Operations Research, INFORMS, vol. 40(3), pages 542-557, March.
    11. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 2022. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2246-2268, November.

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