关键词: Logistic映射, 混沌优化, 组搜索优化, 混沌组搜索优化

Abstract: To improve the performance of Group Search Optimizer (GSO), a new group search optimizer algorithm based on Chaotic Group Search Optimizer (CGSO) in combination with the global searching characteristic of the chaos method was proposed in the paper. In the method, the good position of producer was updated by chaotic searching, the new position of scrounger was determined by the position of producer and the best position which it had been achieved so far, and the new position of rangers was achieved by chaotic mutation. The global convergent performance of GSO was improved by using the initial sensitivity of the Logistic map to expand the scope of the search and by employing the global ergodicity to search the positions. Four function optimization problems were simulated by CGSO and GSO. The experimental results indicate that CGSO is more effective than the others.

Key words: Logistic map, chaos optimization, Group Search Optimizer (GSO), Chaos Group Search Optimizer (CGSO)