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An improved algorithm for the dynamic lot‐sizing problem with learning effect in setups
Author(s) -
Malik Kavindra,
Wang Yufei
Publication year - 1993
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(199312)40:7<925::aid-nav3220400705>3.0.co;2-c
Subject(s) - sizing , computer science , mathematical optimization , variation (astronomy) , function (biology) , algorithm , production (economics) , mathematics , biology , art , physics , macroeconomics , evolutionary biology , astrophysics , economics , visual arts
The dynamic lot‐sizing problem with learning in setups is a variation of the Wagner‐Whitin lot‐sizing problem where the setup costs are a concave, nondecreasing function of the cumulative number of setups. This problem has been a subject of some recent research. We extend the previously studied model to include nonstationary production costs and present an O(T 2 ) algorithm to solve this problem. The worst‐case complexity of our algorithm improves the worst‐case behavior of the algorithms presently known in the literature. © 1993 John Wiley & Sons, Inc.