Studies Of Chaotic Optimization Algorithm And Its Application

Chaos is kind of similar to random movement that generated from nonlinear- uncertainty system. Studies have shown that chaotic sequence was characterized with ergodicity, non-cyclical and randomness etc. As a result of these characteristics, we may introduce the chaos sequence in the optimization field. Since the chaos sequence applied in the optimization field by Li Bing, it has made the rapid development. However, the majority of chaos sequences was limited in generation of Logistic-map, because the sequence generated from Logistic-map was extremely non uniform, a large amount of computing work has been cost. Logistic map, cube mapping and unlimited folded maps were compared in this paper and the characteristics of their chaotic were analyzed, through simulation and statistics, it was found that the last two maps generated the more evenly chaotic sequence and faster search for global optimal solution.Traditional optimization algorithms can perfectly solve the optimization problem of unipolar, however, it was unsatisfied for multi-polar. Chaotic optimization algorithms take its advantages of resolving the problem. In this paper, the traditional and chaotic optimization algorithms were compared, and applied for resolving the multi-target extreme values and mathematical model for the actual economic problems. It was concluded that chaotic optimization algorithms was superior to the traditional. Finally, it was summarized regarding the shortcomings of chaos optimization algorithm and proposed further studies.