An Improved Artificial Bee Colony (ABC) Algorithm with Advanced Search Ability

Abstract

To solve the problem that Artificial Bee Colony (ABC) algorithm is easy to fall into local optimum, this paper proposes an improved Artificial Bee Colony (ABC) algorithm with advanced search ability. This algorithm focuses on adding the number of scouts by comparing the maximum value $Bas_{\max}$, the second largest value $Bas_{second}$ and the third largest value $Bas_{third}$ of $Bas(i)$ with the parameter limit. Inspired by the method of introducing modification rate (MR), the solution generation method of $Bas_{\sec ond}$ is modified to increase disturbance. Six benchmark functions are used to test the efficiency and stability of the algorithm, and the simulation results show the improved ABC algorithm with advanced search ability performs better than ABC algorithm in high dimensional space.