A Comparative Study of Three Lotsizing Methods for theCase of Fuzzy Demand

Most of the literature published regarding the performance of lotsizing algorithms has been in a deterministic environment. The first objective of this article is to propose a way to incorporate fuzzy sets theory into lotsizing algorithms for the case of uncertain demand in a fuzzy master production...

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Bibliographic Details
Published in:International journal of operations & production management 1991-07, Vol.11 (7), p.72-80
Main Authors: Lee, Y.Y., Kramer, B.A., Hwang, C.L.
Format: Article
Language:English
Subjects:
Algorithms
Lot size
Manufacturing
Quantitative techniques
Online Access:Get full text
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Summary:Most of the literature published regarding the performance of lotsizing algorithms has been in a deterministic environment. The first objective of this article is to propose a way to incorporate fuzzy sets theory into lotsizing algorithms for the case of uncertain demand in a fuzzy master production schedule. Triangular fuzzy numbers are used to represent uncertainty in the master production schedule. It is shown that the fuzzy sets theory approach provides a better representation of fuzzy demand and more information to aid the determination of lot size. The second objective is to evaluate three lot sizing methods partperiod balancing, SilverMeal, and WagnerWhitin. The performance of each lotsizing algorithm was calculated over nine examples. The results indicate that the partperiod balancing algorithm may be a better overall choice to determine lot sizes.
ISSN:0144-3577
DOI:10.1108/EUM0000000001276