Modified Artificial Bee Colony Algorithm with Self-Adaptive Extended Memory

To solve the problem of the poor solution precision and convergence speed in the artificial bee colony (ABC) algorithm, in this article we propose a modified algorithm called ABC algorithm with self-adaptive extended memory (ABCSEM) algorithm. First, the extended memory is introduced to store employed bees' historical information comprising recent food sources, personal best food sources, and global best food sources. Furthermore, the extended memory is added to the solution search equation to improve the exploitation capability. Experimental results conducted on a set of numerical benchmark functions show that the ABCSEM algorithm can outperform the ABC algorithm in most of the tested functions.