Research And Improvement Of Bing Bang-Big Crunch Optimization

The Big Bang-Big Crunch (BB-BC), is a new heuristic optimization algorithm proposed by Turkey Osman K. Erol*and Ibrahim Eksin in2006. The algorithm simulates the Big Bang and Contraction theory. The Big Bang and Contraction theory is that:the process of the universe formed is a random distribution of energy dissipation, but also to a local convergence. The BB-BC algorithm is a continuous explosion (Big Bang) and contraction (Big Bang) process, and in this continuous process the algorithm will search the object function solution space in order to find the best fitness value. The algorithm has strong global search ability and convergence speed. With the progress of the research on the theory of algorithms, and its application is more and more widely and has attracted the attention of scholars at home and abroad. But as the algorithm with other global algorithm, are easy to fall into the local optima, the optima precision is not high, there are many points to be improved.This paper introduces the theoretical basis, principle and implementation method of BB-BC in detail, and also analyses the advantages and disadvantages, on this basis, the paper makes improvement on BB-BC and put forward the two kinds of improved algorithm, improvement ability. The main research work of this paper includes:(1) First, introduce swarm intelligence optimization algorithm, lists several common optimization algorithm; Then researches and analyzes the BB-BC, detailed introduces the theoretical knowledge of BB-BC, including the principle, implementation steps, and current research situation.(2) Analysis of the relevant parameters of the BB-BC algorithms, in this paper proposed Chaos Big Bang-Big Crunch algorithm(CBB-BC). CBB-BC algorithm based on Chaos ptimization technology to adjust the shrinkage parameter of the base BB-BC, to prevent the algorithm into a local optimal solution and improve the accuracy of solutions. Through the analysis of experimental results, the CBB-BC algorithm is better than the BB-BC algorithm has faster convergence speed for the low dimensional optimization problem.(3) By introducing the Particle Swarm Optimization(PSO) in CBB-BC, this paper proposed Hybrid Chaos Big Bang-Big Crunch algorithm(HCBB-BC). HCBB-BC in the creation of a new generation of debris by the global optimal solution and has found the best optimal in the iterative process, thereby overcoming the disorder of explosion fragments improve the search ability of the algorithm. Through the analysis of experimental results, the HCBB-BC is the more effective in solving high dimension optimization problems than the BB-BC and CBB-BC.(4) Summarizes the research of this paper and related work, then put forward the next research direction.