Sequential Process Optimisation Using Genetic Algorithms

Show simple item record Oduguwa, Victor en_UK Tiwari, Ashutosh en_UK Roy, Rajkumar en_UK 2006-01-26T12:20:08Z 2006-01-26T12:20:08Z 2004-01 en_UK
dc.identifier.citation Victor Oduguwa, Ashutosh Tiwari, Rajkumar Roy, Sequential Process Optimisation Using Genetic Algorithms, Lecture Notes in Computer Science, Volume 3242, Jan 2004, Pages 782-791 en_UK
dc.identifier.issn 0302-9743
dc.description.abstract Locating 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.extent 1982 bytes
dc.format.extent 440164 bytes
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso en en_UK
dc.publisher Springer-Verlag en_UK
dc.title Sequential Process Optimisation Using Genetic Algorithms en_UK
dc.type Article en_UK

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