A Dynamic Lot-Sizing Model with Demand Time Windows

Authors:
Chung-Yee Lee;Sila Çetinkaya;Albert P. M. Wagelmans
Affiliations:
-;-;-
Venue:
Management Science
Year:
2001

Citing 0
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Abstract

One of the basic assumptions of the classical dynamic lot-sizing model is that the aggregate demand of a given period must be satisfied in that period. Under this assumption, if backlogging is not allowed, then the demand of a given period cannot be deliveredearlier orlater than the period. If backlogging is allowed, the demand of a given period cannot be deliveredearlier than the period, but it can be delivered later at the expense of a backordering cost. Like most mathematical models, the classical dynamic lot-sizing model is a simplified paraphrase of what might actually happen in real life. In most real-life applications, the customer offers a grace period--we call it ademand time window--during which a particular demand can be satisfied with no penalty. That is, in association with each demand, the customer specifies an acceptable earliest and a latest delivery time. The time interval characterized by the earliest and latest delivery dates of a demand represents the corresponding time window.This paper studies the dynamic lot-sizing problem with demand time windows and provides polynomial time algorithms for computing its solution. If backlogging is not allowed, the complexity of the proposed algorithm is O( T2) where T is the length of the planning horizon. When backlogging is allowed, the complexity of the proposed algorithm is O( T3).