Meta-heuristic structure for multiobjective optimization case study: Green sand mould system
In engineering optimization, one often encounters scenarios that are multiobjective (MO) where each of the objectives covers different aspects of the problem. It is hence critical for the engineer to have multiple solution choices before selecting of the best solution. In this chapter, an approach t...
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| Main Authors: | , , , |
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| Format: | Book |
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IGI Global
2014
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946140996&doi=10.4018%2f978-1-4666-5836-3.ch003&partnerID=40&md5=be61758d0e2e53d9e4823ccbd6c705fc http://eprints.utp.edu.my/31291/ |
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| Summary: | In engineering optimization, one often encounters scenarios that are multiobjective (MO) where each of the objectives covers different aspects of the problem. It is hence critical for the engineer to have multiple solution choices before selecting of the best solution. In this chapter, an approach that merges meta-heuristic algorithms with the weighted sum method is introduced. Analysis on the solution set produced by these algorithms is carried out using performance metrics. By these procedures, a novel chaos-based metaheuristic algorithm, the Chaotic Particle Swarm (Ch-PSO) is developed. This method is then used generate highly diverse and optimal solutions to the green sand mould system which is a real-world problem. Some comparative analyses are then carried out with the algorithms developed and employed in this work. Analysis on the performance as well as the quality of the solutions produced by the algorithms is presented in this chapter. © 2014 by IGI Global. All rights reserved. |
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