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

Tao Wu, Leyuan Shi, Joseph Geunes, Kerem Akartunali

Research output: Contribution to journalArticlepeer-review

60 Citations (Scopus)
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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.
Original languageEnglish
Pages (from-to)428-441
Number of pages14
JournalEuropean Journal of Operational Research
Issue number2
Early online date5 May 2011
Publication statusPublished - 16 Oct 2011


  • capacitated
  • multi-level
  • lot-sizing
  • backlogging
  • lower and upper bound guided nested
  • partitions

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