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Handling integrated quantitative and qualitative search space in engineering design optimisation problems

By Victor Oduguwa, Ashutosh Tiwari and Rajkumar Roy


Since information in engineering design problems can be both quantitative (QT) and qualitative (QL) in nature, combining both types of information can result in more realistic solutions for real world optimisation problems. However, most of the approaches reported in the literature are incapable of conducting optimisation searches in such a mixed environment. Therefore this report proposes a mathematically proven methodology for handling integrated QT and QL search space in real world optimisation problems. The report begins by presenting the definition of these optimisation problems, an analysis of the challenges that they pose for existing optimisation strategies and related research. The report then presents the proposed solution strategy and the mathematical proof. Furthermore, a case study on a rod rolling problem is presented to validate the effectiveness of the proposed methodology. The report concludes with a brief outline of limitations and future research activities

Topics: Design optimisation, Evolutionary computing, Qualitative information, Quantitative information, Search space, Rolling system, DEG Report
Year: 2003
OAI identifier:
Provided by: Cranfield CERES

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