A non-random multi-objective cat swarm optimization algorithm based on CAT MAP
作者： Chongfan Luo , Ya'Nan Guo , Yi'De Ma , Chao Lv , Yan Zhang
DOI: 10.1109/ICMLC.2016.7860873
关键词: Mathematical optimization 、 Multi-swarm optimization 、 Metaheuristic 、 Population 、 Meta-optimization 、 Mathematics 、 Particle swarm optimization 、 Derivative-free optimization 、 Swarm behaviour 、 Tracing
摘要: In this paper, a new multi-objective cat swarm optimization algorithm has been proposed. The applies the part of individuals into seeking mode and other tracing non-randomly. Cat map is used to initialize population. way, can avoid trapping local optimal in final iteration process search ability be improved effectively. performance proposed method testified by using 4 test functions. A quantitative assessment carried out several performances metrics compared with previous design methods NSGA-II MOPSO. experiments illustrate that better than algorithms.
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