Multi-Population Artificial Bee Colony (MPABC) Algorithm for Numerical Optimization

2018 3rd International Conference on Insulating Materials, Material Application and Electrical Engineering

材料科学;无线电电子学;电工学

Zhao, Ming^1 ; Wang, Peihong^2

Research Institute of Yunnan Power Grid Co. Ltd., Kunming, Yunnan, China^1

School of Energy and Environment, Southeast University, Jiangsu Province, Nanjing

210096, China^2

关键词: Artificial bee colonies;    Artificial bee colony algorithms;    Artificial bee colony algorithms (ABC);    Local optimizations;    Multi population;    Multiple solutions;    Numerical functions;    Numerical optimizations;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/452/3/032003/pdf
DOI  :  10.1088/1757-899X/452/3/032003

学科分类：材料科学（综合）

来源: IOP

【 摘 要 】

This paper aims to propose a variant artificial bee colony algorithm (ABC), called multi-population artificial bee colony (MPABC) algorithm so as to optimize numerical functions with single and/or multiple solutions where the global optimization can be achieved. In MPABC, the solution space (i.e., food source) is partitioned into some subspaces in which a subpopulation of bees are parallel produced and employed to search the local optimization. Among these local optimizations, the ones with highest adaptability are taken as the global optimizations in each iteration step, and the corresponding local solutions are thus the global solutions. With a reasonable partition of solution space, all the global optimization and all the associated global solutions can be found by using MPABC. This property can not be committed by the ABC, as the ABC is interested in finding the global optimization with one solution in one running time. In addition, the MPABC holds higher abilities on convergence speed and accuracy than the ABC. Some experiments were conducted with some numerical functions so as to validate such conclusions.