A Heuristic Scout Search Mechanism for Artificial Bee Colony Algorithm
Artificial bee colony (ABC) algorithm simulates the foraging behavior of honey bees, which has shown good performance in many application problems and large scale optimization problems. However, the scout foraging behavior in the ABC algorithm is completely random, which would sometimes make it consume more search efforts to discover some promising area and hamper the convergent speed of the ABC algorithm, especially for large scale optimization. To overcome this drawback, this paper proposes a heuristic scout search (HSS) mechanism based on the information obtained during running to guide the scout search. The ABC algorithm with HSS mechanism (HSSABC) has been tested on a set of test functions. Experimental results show that the HSS mechanism can greatly speed up the convergence of the ABC algorithm. After the use of HSS, the performance of the ABC algorithm is significantly improved for both rotated problems and large scale problems.
KeywordsMeta-heuristic Swarm intelligence Artificial bee colony algorithm Continuous optimization