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

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 Basmax, the second largest value Bassecond and the third largest value Basthird of Bas(i) with the parameter limit. Inspired by the method of introducing modification rate (MR), the solution generation method of Bassecond 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.