Sequential process optimisation using genetic algorithms
| dc.contributor.author | Oduguwa, Victor | en_UK |
| dc.contributor.author | Tiwari, Ashutosh | en_UK |
| dc.contributor.author | Roy, Rajkumar | en_UK |
| dc.date.accessioned | 2006-01-26T12:20:08Z | |
| dc.date.available | 2006-01-26T12:20:08Z | |
| dc.date.issued | 2004-01 | en_UK |
| dc.description | Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference, 18-22 September 2004, Birmingham, UK | |
| 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.identifier.citation | Oduguwa V, Tiwari A, Roy R. (2004) Sequential process optimisation using genetic algorithms. In: PPSN VIII. PPSN 2004. Lecture Notes in Computer Science, Volume 3242. Springer, Berlin. January 2004, pp. 782-791 | en_UK |
| dc.identifier.issn | 0302-9743 | |
| dc.identifier.uri | http://hdl.handle.net/1826/994 | |
| dc.language.iso | en | en_UK |
| dc.publisher | Springer | en_UK |
| dc.title | Sequential process optimisation using genetic algorithms | en_UK |
| dc.type | Article | en_UK |