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Algorithms and heuristics for variable‐yield lot sizing
Author(s) -
Mazzola Joseph B.,
McCoy William F.,
Wagner Harvey M.
Publication year - 1987
Publication title -
naval research logistics (nrl)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.665
H-Index - 68
eISSN - 1520-6750
pISSN - 0894-069X
DOI - 10.1002/1520-6750(198702)34:1<67::aid-nav3220340107>3.0.co;2-r
Subject(s) - economic order quantity , heuristics , sizing , mathematical optimization , heuristic , computer science , variable (mathematics) , stockout , inventory control , production (economics) , holding cost , yield (engineering) , operations research , mathematics , economics , supply chain , microeconomics , art , mathematical analysis , materials science , visual arts , metallurgy , political science , law
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.