Adaptive bacterial foraging optimization algorithm
Jiang Jian-gu · Journal of Xidian University · 2015
An adaptive bacterial foraging optimization algorithm is presented due to the classic optimization algorithm's poor performance when optimizing high-dimensional complex functions.The fixed chemotactic step is improved as the adaptive sliding step which decreases nonlinearly with the result of strengthening the ability of local search.The adaptive dimension learning method for the optimal bacterium in the current cycle of chemotaxis is proposed so as to increase the accuracy of the solution and enhance the search efficiency.The elite bacterium is used as the initial point for Tent chaotic mapping to initialize the position of bacteria which meet the conditions of migration,and therefore the convergence speed of the algorithm is accelerated.Experimental result indicates that the algorithm outperforms the classic algorithm both in terms of solution accuracy and convergence speed.And,the algorithm has a higher efficiency.