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Sequential Process Optimisation Using Genetic Algorithms

By Victor Oduguwa, Ashutosh Tiwari and Rajkumar Roy


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

Publisher: Springer-Verlag
Year: 2004
OAI identifier:
Provided by: Cranfield CERES

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