{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,2,29]],"date-time":"2024-02-29T10:43:46Z","timestamp":1709203426757},"reference-count":23,"publisher":"University of Zielona G\u00f3ra, Poland","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007,3,1]]},"abstract":"Hybrid Approach to Design Optimisation: Preserve Accuracy, Reduce Dimensionality<\/jats:title>The paper proposes a design procedure for the creation of a robust and effective hybrid algorithm, tailored to and capable of carrying out a given design optimisation task. In the course of algorithm creation, a small set of simple optimisation methods is chosen, out of which those performing best will constitute the hybrid algorithm. The simplicity of the method allows implementing ad-hoc modifications if unexpected adverse features of the optimisation problem are found. It is postulated to model a system that is smaller but conceptually equivalent, whose model is much simpler than the original one and can be used freely during algorithm construction. Successful operation of the proposed approach is presented in two case studies (power plant set-point optimisation and waveguide bend shape optimisation). The proposed methodology is intended to be used by those not having much knowledge of the system or modelling technology, but having the basic practice in optimisation. It is designed as a compromise between brute force optimisation and design optimisation preceded by a refined study of the underlying problem. Special attention is paid to cases where simulation failures (regardless of their nature) form big obstacles in the course of the optimisation process.<\/jats:p>","DOI":"10.2478\/v10006-007-0006-3","type":"journal-article","created":{"date-parts":[[2007,4,11]],"date-time":"2007-04-11T22:05:46Z","timestamp":1176329146000},"page":"53-71","source":"Crossref","is-referenced-by-count":0,"title":["Hybrid Approach to Design Optimisation: Preserve Accuracy, Reduce Dimensionality"],"prefix":"10.61822","volume":"17","author":[{"given":"Mariusz","family":"Kamola","sequence":"first","affiliation":[]}],"member":"37438","reference":[{"key":"1","volume-title":"Nonlinear Programming","author":"M. Bazaraa","year":"1993"},{"issue":"1","key":"2","doi-asserted-by":"crossref","first-page":"42","DOI":"10.1093\/comjnl\/8.1.42","article-title":"A new method of constrained optimization and a comparison with other methods","volume":"8","author":"M. Box","year":"1965","journal-title":"Comput. 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