Accelerating artificial bee colony algorithm with neighborhood search

Abstract

In this paper, we integrate variable neighborhood search (VNS) into artificial bee colony (ABC) algorithm so that the search ability under variable neighborhood structures and local search is accelerated. Two VNS methods, including the reduced VNS and basic VNS, are integrated to develop different versions. The proposed algorithm, named variable neighborhood ABC (VNABC), is verified in a comprehensive set of benchmark functions. The experimental results confirm that VNABC outperforms the state-of-the-art ABC and differential evolution (DE) algorithms in terms of the convergence speed.