Name
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). |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1287/mnsc.47.10.1384.10259 | Management Science |
Keywords | Field | DocType |
demand time windows,latest delivery time,dynamic lot-sizing model,corresponding time window,particular demand,time windows,polynomial time algorithm,proposed algorithm,lot-sizing,classical dynamic lot-sizing model,ademand time window,dynamic programming,aggregate demand,grace period,demand,inventory control,mathematical model,management science,mathematical optimization,algorithms,satisfiability,mathematical models | Dynamic programming,Economics,Mathematical optimization,Time horizon,Paraphrase,Inventory control,Sizing,Aggregate demand,Mathematical model,Time complexity | Journal |
Volume | Issue | ISSN |
47 | 10 | 0025-1909 |
Citations | PageRank | References |
30 | 2.14 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chung Yee Lee | 1 | 1701 | 172.81 |
| Sila Çetinkaya | 2 | 144 | 13.01 |
| Albert P. M. Wagelmans | 3 | 375 | 30.12 |