COORDINATE MULTI-POPULATION GENETIC ALGORITHMS FOR MULTI-MODAL FUNCTION OPTIMIZATION
多模态函数优化的协同多群体遗传算法

Traditional GA adopts crowding or fitness-sharing technique to evolve multi-solutions in a single population, which does not conform to the natural evolution of species and is also with the difficulty of parameters design. We analyze the characteristics of GA evolution of population and species evolution in nature, and formulate the logic of macro-niching method based on multi-populations, and describe its work flow in detail. Moreover, we design a new algorithm for calculating niche radius automatically. Finally, the coordinate multi-population GA is applied to the optimizations of typical multi-modal functions, and the experiments reveal its efficiency and effectiveness.