A Study on Bacterial Colony Chemotaxis Algorithm and Simulation Based on Differential Strategy

摘要

Bacterial Colony Chemotaxis (BCC) algorithm is a new colony Intelligence Optimization Algorithm.In this paper through a mass of experiments on the standard test function,the impact of the algorithm parameters on the performance of algorithm is demonstrated,then the parameter control strategy are given,which laid the foundation for further study of the algorithm.To further enhance success rate of BCC algorithm on multi-modal function,two improvements are presented,one is adjusting the sense limit (SL) self-adaptive,and the other is introducing differential evolutionary strategy into algorithm.The numerical experiment's results using Matlab show that the performances of the improved BCC algorithm have been enhanced both in success rate and convergence precision.Finally the algorithm is applied to the optimal planning of substation locating,and achieves the satisfactory results.