Solving Multimodal problems by Coincidence Algorithm

In general, Multimodal optimization is hard problems even for Evolutionary Algorithm. Using a Genetic Algorithm (GA) to solve these problems, the algorithm cannot converge to solutions easily. This work presents a study of Coincidence Algorithm (COIN) to solve these problems. COIN has an ability to retain multiple solutions in its model; hence it is suitable for Multimodal optimization problems. The experiment is carried out to illustrate this capability. The benchmarks are designed for comparing the problem solving behavior of COIN against a Genetic Algorithm.