KBLS - A PROTOTYPE KNOWLEDGE-BASED SYSTEM FOR THE SELECTION OF LOT-SIZING MODELS

被引:1
|
作者
GUPTA, YP
KEUNG, YK
机构
[1] UNIV LOUISVILLE,DEPT MANAGEMENT,LOUISVILLE,KY 40292
[2] UNIV MANITOBA,DEPT ACTUARIAL & MANAGEMENT SCI,WINNIPEG R3T 2N2,MANITOBA,CANADA
关键词
LOT-SIZING; EXPERT SYSTEM; TANDEM ARCHITECTURE;
D O I
10.1007/BF01471107
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Research in experimental simulation of multi-stage inventory systems shows that a poor choice of lot-sizing heuristics has a significant degree of cost penalty and schedule instability. A realistic approach to a multi-stage system is to choose a suitable technique for a certain special circumstance rather than trying for a single best heuristic covering all cases. To avoid serious cost penalties and high schedule instability caused by inferior techniques, knowledge-based system technology could help practitioners to make a sensible choice of heuristics. In this paper, we develop a prototype knowledge-based system whose aim is to provide an acceptable lot-size schedule in a limited time which would hopefully lead to a good master production schedule.
引用
收藏
页码:199 / 211
页数:13
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