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An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging

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  • Wu, Tao
  • Shi, Leyuan
  • Geunes, Joseph
  • AkartunalI, Kerem

Abstract

This paper proposes two new mixed integer programming models for capacitated multi-level lot-sizing problems with backlogging, whose linear programming relaxations provide good lower bounds on the optimal solution value. We show that both of these strong formulations yield the same lower bounds. In addition to these theoretical results, we propose a new, effective optimization framework that achieves high quality solutions in reasonable computational time. Computational results show that the proposed optimization framework is superior to other well-known approaches on several important performance dimensions.

Suggested Citation

  • Wu, Tao & Shi, Leyuan & Geunes, Joseph & AkartunalI, Kerem, 2011. "An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging," European Journal of Operational Research, Elsevier, vol. 214(2), pages 428-441, October.
    • Handle: RePEc:eee:ejores:v:214:y:2011:i:2:p:428-441
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    8. Wu, Tao & Xiao, Fan & Zhang, Canrong & Zhang, Defu & Liang, Zhe, 2019. "Regression and extrapolation guided optimization for production–distribution with ship–buy–exchange options," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 15-37.
    9. Almeder, Christian & Klabjan, Diego & Traxler, Renate & Almada-Lobo, Bernardo, 2015. "Lead time considerations for the multi-level capacitated lot-sizing problem," European Journal of Operational Research, Elsevier, vol. 241(3), pages 727-738.
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