A Survey of Artificial Bee Colony Algorithm

Abstract

Artificial bee colony algorithm (ABC) is a novel biological heuristic optimization paradigm inspired by the honeybee foraging behaviors. And it has received a surge of attention due to its merits of a simplified model, fewer control parameters, and strong robustness. This paper firstly introduces the basic biological principles and mathematical operators of ABC, and then comprehensively presents and analyzes the recent significant research on ABC with aspects of algorithm improvements and engineering applications. Specifically, several representative improvement models and strategies are summarized, and its extended versions including discrete ABC and multi-objective ABC are introduced in detail. Furthermore, its typical applications on neural network training, wireless network, image processing, wireless network, and scheduling are summarized. Finally, we propose our views about the challenges and further research highlights of ABC.