A New Coati Optimization Algorithm for Binary Optimization

Coati Optimization Algorithm (COA) is a recently proposed heuristic optimization algorithm. The COA establishes phrases of exploitation and exploration by mimicking coati behavior. A comparison with twelve well-known optimization algorithms demonstrates the robustness of the COA. However, it can only be directly applied to continuous problems and its application in binary problems has not been well implemented. Therefore, a binary version (BCOA) is proposed in this paper. In BCOA, the positions of individuals in discrete space are mapped using sigmoid and V-shaped transfer functions. In addition, two experiments are underway to test the performance of BCOA. The comparison with the five optimization algorithms of the CEC2013 suite proved that BCOA has better optimization ability. Finally, this paper performed a Wilcoxon rank-sum test at a 5% significance level. The test shows that the proposed BCOA significantly outperforms the other algorithms.