Abstract:

Continuous ant colony optimization is an important research direction of ant colony optimization algorithms. The ant colony optimization for continuous domains (ACOR) requires long computation time and is easily trapped into local optimal solutions, so we propose artificial bee colony based ant colony optimization for continuous domain algorithm (ABCACOR) to solve the problems. Firstly, an alternative mechanism instead of the original sortbased selection method is introduced to guide solution choice, which saves computation time and secures the diversity as long as possible. Secondly, the artificial bee colony search strategy is adopted to improve the  global search ability of the algorithm, thus the computation time is further reduced and the accuracy of solutions is improved. We evaluate the ABCACOR on a large number of test functions, and experimental results show that the ABCACOR outperforms some existing continuous ant colony optimization algorithms.

Key words: ant colony optimization algorithm;continuous domain;artificial bee colony;global search;alternative mechanism