Robust inventory control under lead time uncertainty

Andreas Thorsen, Hongcheng Liu, Tao Yao

Research output: Contribution to conferencePaperpeer-review

Abstract

Many real world supply chains involve uncertain order lead times which impacts order policies. The Robust Optimization paradigm has been established as a modeling approach for problems that involve such uncertainties and is tractable for several classes of problems. We present a robust optimization model of a multi-period inventory control problem for a retailer under lead time uncertainty. A polyhedral lead time uncertainty set is devised by parameterizing the lead time of orders at each time period. We show that this problem is an application of robust optimization under column-wise uncertainty, with uncertainty characterized by the coefficients for orders at each time period. As a result, the standard robust optimization reformulation technique utilizing duality cannot be used for these problems. Instead, a variation of Benders' decomposition is used to determine optimal robust (i.e., best worst-case) policy parameters under two policies (static and basestock). The computational performance of the algorithm is particularly good for the basestock policy, capable of solving problem instances with 100 time periods in thirty seconds.

Original languageEnglish (US)
Pages3869-3878
Number of pages10
StatePublished - Jan 1 2013
EventIIE Annual Conference and Expo 2013 - San Juan, Puerto Rico
Duration: May 18 2013May 22 2013

Other

OtherIIE Annual Conference and Expo 2013
CountryPuerto Rico
CitySan Juan
Period5/18/135/22/13

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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