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Algorithms and heuristics for variable-yield lot sizing
Authors:Joseph B. Mazzola  William F. McCoy  Harvey M. Wagner
Affiliation:1. Fuqua School of Business, Duke University, Durham, North Carolina 27706;2. J. P. Morgan Investment Management 9 West 57th Street New York, New York 10019;3. Graduate School of Business Administration, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514
Abstract:We consider the multiperiod lot-sizing problem in which the production yield (the proportion of usable goods) is variable according to a known probability distribution. We review two economic order quantity (EOQ) models for the stationary demand continuous-time problem and derive an EOQ model when the production yield follows a binomial distribution and backlogging of demand is permitted. A dynamic programming algorithm for an arbitrary sequence of demand requirements is presented. Heuristics based on both the EOQ model and appropriate modification of the underlying perfect-yield lot-sizing policies are discussed, and extensive computational evaluation of these heuristics is presented. Two of these heuristics are then modified to include the notion of supply safety stock. The modified heuristics consistently produce near-optimal lot-sizing policies for problems with stationary and time-varying demands.
Keywords:
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