Abstract
The present paper proposes and studies the efficiency of using a RSM enhanced ACOR algorithm for the optimization of electromagnetic devices. Different RSM methods, such as Box-Behnken, CCD and Doelhert, are applied to find most suitable parameters (optimal set) for the ACOR in order to solve the corresponding electromagnetic optimization problems. The parameters optimal set is found by building a metaheuristic function. In the same time, the optimal parameter set is searched and determined for each electromagnetic problems for different objective functions, the best and the average global best solution for a tests set. The electromagnetic devices to be optimized are the Loney’s solenoid and an energy storage device, as defined by the TEAM22 problem. Both electromagnetic problems are proposed benchmarks from electromagnetic community
Reference21 articles.
1. "[1] M. Dorigo, V. Maniezzo and A. Colorni, Ant system: optimization by a colony of cooperating agents, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 26(1), pp. 29-41, 1996.
2. [2] T. Stutzle, and H. Hoos, MAX-MIN ant system and local search for the traveling salesman problem, IEEE Evolutionary Computation, pp. 309-314, 1997.
3. [3] M. Dorigo, and G. Di Caro, Ant colony optimization: a new metaheuristic, Proceedings of the Congress on Evolutionary Computation, pp. 1470-1477, 1999.
4. [4] E. Ridge, and D. Kudenko. Tuning the performance of the MMAS heuristic. In Engineering stochastic local search algorithms. designing, implementing and analyzing effective heuristics, pp. 46- 60. Springer, Berlin, Heidelberg, 2007.
5. [5] S. Fidanova,, Ant colony optimization and multiple knapsack problem. In Handbook of Research on Nature-Inspired Computing for Economics and Management, pp. 498-509. IGI Global, 2007.