Tan, Tun Tai (2009) A Method For Solving Mult-Objective Optimization Problem: Vector Evaluated Genetic Algorithm (Vega). [Final Year Project Report] (Unpublished)
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Abstract
Solving Multi-Objective Optimization Problem (MOOP) is significant as it finds solutions that satisfy two or more objectives simultaneously which are always related to the real world situation. However, it is impractical to solve MOOP by using classical methods due to its complexity. Genetic Algorithms (GAs) are a powerful stochastic search in solving optimization problems. Nonetheless, GAs which always deal with single objective cannot be used to solve MOOP. Consequently, some components of GAs had been modified to produce Vector Evaluated Genetic Algorithm (VEGA) in order to adapt the nature of MOOP. Simulation runs on GAs and VEGA are developed to demonstrate their capability in solving optimization problems. Series of experiment are done on VEGA in order to find out its performance under various parameter input. The results are later compared.
| Item Type: | Final Year Project Report |
|---|---|
| Additional Information: | Project report (B.Sc.) -- Universiti Malaysia Sarawak, 2009. |
| Uncontrolled Keywords: | optimization problems, Genetic Algorithms (GAs), Vector Evaluated Genetic Algorithm |
| Subjects: | H Social Sciences > H Social Sciences (General) Q Science > Q Science (General) |
| Divisions: | Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development Faculties, Institutes, Centres > Faculty of Cognitive Sciences and Human Development Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development |
| Depositing User: | Patrick |
| Date Deposited: | 05 Feb 2025 07:45 |
| Last Modified: | 05 Feb 2025 07:45 |
| URI: | http://ir.unimas.my/id/eprint/47511 |
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