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. © Springer-Verlag 2004.
CITATION STYLE
Oduguwa, V., Tiwari, A., & Roy, R. (2004). Sequential process optimisation using genetic algorithms. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3242, 782–791. https://doi.org/10.1007/978-3-540-30217-9_79
Mendeley helps you to discover research relevant for your work.