A Comparative Study of Three Lot‐sizing Methods for the Case of Fuzzy Demand

Abstract

Most of the literature published regarding the performance of lot‐sizing 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: part‐period balancing, Silver‐Meal, and Wagner‐Whitin. The performance of each lot‐sizing algorithm was calculated over nine examples. The results indicate that the part‐period balancing algorithm may be a better overall choice to determine lot sizes.

Citation

Lee, Y.Y., Kramer, B.A. and Hwang, C.L. (1991), "A Comparative Study of Three Lot‐sizing Methods for the Case of Fuzzy Demand", International Journal of Operations & Production Management, Vol. 11 No. 7, pp. 72-80. https://doi.org/10.1108/EUM0000000001276