2024-03-29T01:25:34Zhttps://weko.wou.edu.my/?action=repository_oaipmhoai:weko.wou.edu.my:000004982015-09-30T17:08:21Z00025
Research review: a modified micro genetic algorithm for undertaking multi-objective optimization problemsengMulti-objective optimizationMicro genetic algorithmhttp://weko.wou.edu.my/?action=repository_uri&item_id=498Learning MaterialTan, Choo JunA Modified micro Genetic Algorithm (MmGA) is proposed for undertaking Multi-objective Optimization Problems (MOPs). An NSGA-II inspired elitism strategy and a population initialization strategy are embedded into the traditional micro Genetic Algorithm (mGA) to form the proposed MmGA. The main aim of the MmGA is to improve its convergence rate towards the pareto optimal solutions. To evaluate the effectiveness of the MmGA, two experiments using the Kursawe test function in MOPs are conducted, and the results are compared with those from other approaches using a multi-objective evolutionary algorithm indicator, i.e. the Generational Distance (GD). The outcomes positively demonstrate that the MmGA is able to provide useful solutions with improved GD measures for tackling MOPs. Electronic https://weko.wou.edu.my/?action=repository_action_common_download&item_id=498&item_no=1&attribute_id=15&file_no=1CC BY-NC-SAWawasan Open University2014-12-12