A Hybrid Evolutionary Imperialist Competitive Algorithm (HEICA)

This paper proposes a new approach by combining the Evolutionary Algorithm and Imperialist Competitive Algorithm. This approach tries to capture several people involved in community development characteristic. People live in different type of communities: Monarchy, Republic and Autocracy. People dominion is different in each community. Research work has been undertaken to deal with curse of dimensionality and to improve the convergence speed and accuracy of the basic ICA and EA algorithms. Common benchmark functions and large scale global optimization have been used to compare HEICA with ICA, EA, PSO, ABC, SDENS and jDElsgo. HEICA indeed has established superiority over the basic algorithms with respect to set of functions considered and it can be employed to solve other global optimization problems, easily. The results show the efficiency and capabilities of the new hybrid algorithm in finding the optimum. Amazingly, its performance is about 85% better than others. The performance achieved is quite satisfactory and promising.