Article ID: | iaor20011774 |
Country: | Netherlands |
Volume: | 38 |
Issue: | 2 |
Start Page Number: | 283 |
End Page Number: | 296 |
Publication Date: | Jul 2000 |
Journal: | Computers & Industrial Engineering |
Authors: | Li Y., Ip W.H., Man K.F., Tang K.S. |
Keywords: | genetic algorithms |
Earliness and tardiness production scheduling and planning (ETPSP) have been studied by a number of researches in recent years. However, the existing researches have been limited to the study of machine scheduling, and the effects of multi-product production, with the considerations of machine scheduling and lot-size and capacity not being investigated. One of the reasons for this is the complexity of solving large-scale discrete problems where restrictions of linearity, convexity and differentiability prevail. Classical optimization methods have proved inadequate and an alternative approach is investigated here. A new extensive model of ETPSP is developed in this paper to address the multi-product production environment. A genetic alogrithm (GA) is applied in order to obtain an optimal solution for this large-scale problem. The investigation demonstrates the use of a comprehensive model to represent a real life manufacturing environment and illustrates the fact that a solution can be effectively and efficiently obtained using the GA approach.