Social-Based Algorithm (SBA)

This paper proposes a new approach by combining the Evolutionary Algorithm (EA) and socio-political process based Imperialist Competitive Algorithm (ICA). This approach tries to capture several people involved in community development characteristic. People live in different type of communities: Monarchy, Republic, Autocracy and Multinational. Leadership styles are 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. The proposed algorithm has been compared with some well-known heuristic search algorithms. The obtained results confirm the high performance of the proposed algorithm in solving various benchmark functions specially in high dimensional problem. Simulation results were reported and the SBA 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 other algorithms such as EA and ICA. The performance achieved is quite satisfactory and promising for all test functions.

Figure optionsDownload as PowerPoint slideHighlights
► We model human social communities which have been used for optimization. This model is combination of Evolutionary Algorithm and Imperialist Competitive Algorithm.
► We try to capture several people involved in community development characteristic.
► We model different types of communities: Monarchy, Republic, Autocracy and Multinational.
► We examine novel hybrid optimization algorithm for different benchmark functions.
► Using novel algorithm will increase quality of results.