Self-adaptive search equation-based artificial bee colony algorithm with CMA-ES on the noiseless BBOB testbed
Doğan Aydin, Gürcan Yavuz · Proceedings of the Genetic and Evolutionary Computation Conference Companion · 2017
Self-Adaptive Search Equation based Artificial Bee Colony (SSEABC) is a recent variant of Artificial Bee Colony (ABC) algorithm. SSEABC proposed three enhancements on the canonical ABC algorithm. These are the self-adaptive search equation selection strategy, hybridization with a local search procedure and incremental population size strategy. The performance of SSEABC is tested on CEC 2015 benchmark suite and ranked third within all participants of competition. In this paper, we benchmark SSEABC using the noise-free BBOB function testbed. We also compare SSEABC performance to PSO, ABC and GA algorithms.