KNOWLEDGE BASED SCHEDULING SYSTEMS - A FRAMEWORK

被引:5
作者
JOHNSON, LM [1 ]
DILEEPAN, P [1 ]
SEN, T [1 ]
机构
[1] UNIV TENNESSEE,DEPT MANAGEMENT,CHATTANOOGA,TN 37403
关键词
PRODUCTION SCHEDULING; ARTIFICIAL INTELLIGENCE; EXPORT SYSTEMS; SIMULATION;
D O I
10.1007/BF01472508
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Scheduling is a complex problem which occurs often in a manufacturing environment. There are many possible variations within the context of a scheduling problem, enough to overwhelm anyone but an expert. A production manager, faced with the task of job scheduling for a particular process, might well benefit from the advice of a scheduling expert. Even though the scheduling literature is full of optimizing rules for a variety of manufacturing environments few, if any, of these rules have been used in practice. The bewildering variety of theoretical results, the lack of a mechanism to match theoretical results to practical problems and the difficulty in establishing the practical efficacy of the theoretical results are among the reasons for this gap between scheduling theory and practice. This paper describes a scheduling expert system framework which addresses these problems and helps bridge this gap. The solution techniques available in SCHEDEX produce a specific schedule for the problem according to a procedure which has been mathematically proven to provide a satisfactory and often optimal solution, given the criteria for the problem. A simulation model also tests for the effectiveness of a selected technique with respect to the chosen performance measure(s).
引用
收藏
页码:117 / 123
页数:7
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