Cultural Based Particle Swarm Optimization To Layout Design

This thesis mainly focus on the research of Particle Swarm Optimization(PSO) algorithm and its application in layout scheme design, its engineering background is complex layout design problem, such as: the layout design of satellite cabin, VLSI parts layout design etc. The layout design problem is a combinational optimization problem with NP-hard in viewpoint of math theory; practically it has a broad background and application value.The layout design problem absorbs the eyes of researchers in sciences and industries in a long term and many applicable algorithms have been developed, such as: heuristic algorithm, graph theory method, evolutionary computing etc. The research of layout design problem solving has never been stopped for no one algorithm can dominate the others. PSO is" a new evolutionary computing technique, with the strongpoint of simple computing and robustness. It has been successfully applied in many fields, but it still has the weakness of easily got struck in local optimum and weak global search ability. For overcome its weakness, this thesis proposes the Cultural-Based PSO algorithm (CBPSO) after well study the PSO and cultural algorithms.The main contents for this thesis are as follows:(1) Cultural-based PSO algorithm is proposed in this thesis. This algorithm embeds PSO into the cultural algorithm framework; compose an algorithm with PSO main population space and belief space. The two spaces own their populations and evolve independently and parallel; and make the belief space guide the search in main population space at the right time for sake of enhancing the global search ability of PSO.(2) Making numerical simulation experiments with numerical examples. Aiming at the layout problems of satellite cabin and integrated circuit, to establish the simplied math model and describe the layout problem and applied the CBPSO method to solve this problem. And compare the result of CBPSO with that of PSO algorithm and GA. The results show that CBPSO is feasible and effective, which is better than PSO, and each has his strong point compared with GA.This research and proposed method not only benefit the development of techniques in related fields theoretically, but it can be applied to practical application. Moreover, it makes reference for further research in this field.The research of this thesis is financially supported by National Natural Science Foundation of China (No. 50335040,50275019).