Hopfield neural network approach for single machine scheduling problem

被引：0

作者：

Maheswaran, R ^{[1
]}

Ponnambalam, SG ^{[1
]}

Samuel, DN ^{[1
]}

Ramkumar, AS ^{[1
]}

机构：

[1] Mepco Shlenk Engn, Dept Mech Engn, Sivakasi 626005, India

来源：

2004 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2 | 2004年

关键词：

Hopfield Neural network; single machine total; weighted tardiness problem; binary representation;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a Hopfield neural network approach for the problem of scheduling n jobs in a single machine to minimize total weighted tardiness. A binary encoding scheme is introduced to represent the solutions, together with a heuristic to decode. A 10-job problem is solved by sequencing the job using different methods viz. weighted shortest processing time (WSPT) rule, Earliest Due Date (EDD) rule, binary representation and Hopfield Neural Network. The results show that the Hopfield neural network performs better over others.

引用

页码：850 / 854

页数：5

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