THE EFFECT OF TIME-VALUE OF MONEY ON DISCRETE TIME-VARYING DEMAND LOT-SIZING MODELS WITH LEARNING AND FORGETTING CONSIDERATIONS

Abstract

In this paper, we consider the problem of incorporating learning, forgetting, and the time-value of money into discrete time-varying demand lot-sizing models to determine lot sizes and relevant costs. The occurrence of forgetting is caused by a break between two intermittent production runs which leads to retrogression in learning and loss of labor productivity. A present value approach is used to discount the stream of future cost flows. This paper extends the original Wagner-Whitin algorithm and the classical EOQ model to models in which the effects of learning, forgetting, and the time-value of money are considered simultaneously. Numerical examples and computational results indicate that corresponding parameters for the three effects have significant effects on the determination of lot sizes and relevant costs. Comparisons among models with and without the three effects are also made.