Robust Approximation to Multiperiod Inventory Management

Chuen-Teck See () and Melvyn Sim ()
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Chuen-Teck See: Department of Industrial and Systems Engineering, National University of Singapore (NUS), Singapore
Melvyn Sim: NUS Business School, Singapore-MIT Alliance, NUS Risk Management Institute, Singapore

Operations Research, 2010, vol. 58, issue 3, 583-594

Abstract: We propose a robust optimization approach to address a multiperiod inventory control problem under ambiguous demands, that is, only limited information of the demand distributions such as mean, support, and some measures of deviations. Our framework extends to correlated demands and is developed around a factor-based model, which has the ability to incorporate business factors as well as time-series forecast effects of trend, seasonality, and cyclic variations. We can obtain the parameters of the replenishment policies by solving a tractable deterministic optimization problem in the form of a second-order cone optimization problem (SOCP), with solution time; unlike dynamic programming approaches, it is polynomial and independent on parameters such as replenishment lead time, demand variability, and correlations. The proposed truncated linear replenishment policy (TLRP), which is piecewise linear with respect to demand history, improves upon static and linear policies, and achieves objective values that are reasonably close to optimal.

Keywords: robust optimization; inventory control (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (55)

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