Artificial Bee Colony Algorithm with Good Point Set and Turn Process of Monkey Algorithm
LIU Xiang-Pin1, XUAN Shi-Bin1,2, LIU Feng1
1.College of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006 2. Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis, Guangxi University for Nationalities, Nanning 530006
Abstract：An improved Artificial Bee Colony (ABC) algorithm with good point set and turn process of Monkey algorithm (MA) is proposed to overcome the defections of the basic ABC algorithm. Firstly, aiming at the defects of premature convergence, the good point set is used to initialize the population, which can generate a homogeneous population to keep the diversity of a swarm. Besides, the turn process of MA is introduced to help the swarm to jump out of the local optima and to get the global optimal solution.Simulation results on standard test functions and benchmark functions of CEC05 show that the proposed algorithm outperforms the basic algorithm and other improved ABC algorithms on both the precision and the convergence rate.
刘香品，宣士斌，刘峰. 引入佳点集和猴群翻过程的人工蜂群算法*[J]. 模式识别与人工智能, 2015, 28(1): 80-89.
LIU Xiang-Pin, XUAN Shi-Bin, LIU Feng. Artificial Bee Colony Algorithm with Good Point Set and Turn Process of Monkey Algorithm. , 2015, 28(1): 80-89.
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2015, Vol. 28 
