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Hopfield neural network approach for single machine scheduling problem

Publication Type : Conference Paper

Publisher : IEEE Conference on Cybernetics and Intelligent Systems

Source : 2004 IEEE Conference on Cybernetics and Intelligent Systems, p.849-853 (2004)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-11244269738&partnerID=40&md5=ea829fdca1af06c22d665f6771c615a1

ISBN : 9780780386440

Keywords : Binary representation, Binary sequences, decision making, Earliest due date (EDD), Hopfield neural networks, Image coding, Neural networks, Problem solving, Scheduling, Single machine total weighted tardiness problem, Terminology

Year : 2004

Abstract : 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.

Cite this Research Publication : Ra Maheswaran, Ponnambalam, S. Gb, Samuel, D. Na, and Ramkumar, A. Sc, “Hopfield neural network approach for single machine scheduling problem”, in 2004 IEEE Conference on Cybernetics and Intelligent Systems, 2004, pp. 849-853.

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