Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19133
Title: Multi-product planning and scheduling using genetic algorithm approach
Authors: Ip, WH 
Li, Y
Man, KF
Tang, KS
Issue Date: 2000
Publisher: Pergamon Press
Source: Computers and industrial engineering, 2000, v. 38, no. 2, p. 283-296 How to cite?
Journal: Computers and industrial engineering 
Abstract: Earliness and tardiness production scheduling and planning (ETPSP) have been studied by a number of researchers 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 are 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 algorithm (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.
URI: http://hdl.handle.net/10397/19133
ISSN: 0360-8352
EISSN: 1879-0550
DOI: 10.1016/S0360-8352(00)00044-9
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