Artificial bee colony algorithm (ABC), a heuristic algorithm motivated by the forging behavior of bee swarm, is competent to solve complex engineering problems yet imperfect in its exploitation process. For higher convergence speed and better searching accuracy, we propose balancing evolution strategy as an amendment, which seeks to balance local exploration and global exploitation. In this paper, variable crossover & mutation method and clustering selection approach mainly constitute this strategy. We elaborate on the mechanism of BE-ABC and release its convergence proof by adopting the finite covering theorem in mathematical analysis. After simulating on several benchmark functions, we preliminarily confirm that BE-ABC is capable to converge more efficiently in comparison with some relevant algorithms.
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