Sequential process optimisation using genetic algorithms

dc.contributor.authorOduguwa, Victoren_UK
dc.contributor.authorTiwari, Ashutoshen_UK
dc.contributor.authorRoy, Rajkumaren_UK
dc.date.accessioned2006-01-26T12:20:08Z
dc.date.available2006-01-26T12:20:08Z
dc.date.issued2004-01en_UK
dc.description.abstractLocating good design solutions within a sequential process environment is necessary to improve the quality and overall productivity of the processes. Multi-objective, multi-stage sequential process design is a complex problem involving large number of design variables and sequential relationship between any two stages. The aim of this paper is to propose a novel framework to handle real-life sequential process optimisation problems using a Genetic Algorithm (GA) based technique. The research validates the proposed GA based framework using a real-life case study of optimising the multi-pass rolling system design. The framework identifies a number of near optimal designs of the rolling system.en_UK
dc.format.extent1982 bytes
dc.format.extent440164 bytes
dc.format.mimetypetext/plain
dc.format.mimetypeapplication/pdf
dc.identifier.citationOduguwa V, Tiwari A, Roy R. (2004) Sequential process optimisation using genetic algorithms. Lecture Notes in Computer Science, Volume 3242, January 2004, pp. 782-791en_UK
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/1826/994
dc.language.isoenen_UK
dc.publisherSpringer-Verlagen_UK
dc.titleSequential process optimisation using genetic algorithmsen_UK
dc.typeArticleen_UK

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