Multi-product planning and scheduling using genetic algorithm approach

被引:40
|
作者
Ip, WH [1 ]
Li, Y
Man, KF
Tang, KS
机构
[1] Hong Kong Polytech Univ, Dept Mfg Engn, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Dept Elect Engn, Hong Kong, Peoples R China
关键词
production scheduling and planning; genetic algorithm; MRP/ERP; JIT;
D O I
10.1016/S0360-8352(00)00044-9
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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. (C) 2000 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:283 / 296
页数:14
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