Abstract
In this paper, a new metaheuristic, Electric Charged Particles Optimization (ECPO) algorithm, is developed. This algorithm is inspired by the interaction (forces exerted) between electric charged particles. It this algorithm not all the particles interact with each other, only selected ones. Then the way they interact with each other is defined by the selected strategy among the three available strategies. Therefore, there are several combinations possible between the number of interacting particles and strategies to find the most suitable one for the problem in hand which will help the algorithm to solve a wide range of optimization problems. The performance of the developed algorithm is first tested on the set of problems used for single objective real parameter algorithm competition that was held in the congress on evolutionary computation 2014. Then, the ECPO has been applied to optimal design of circular antenna array for sidelobe level reduction. The obtained results are then compared with other well-known metaheuristics using statistical tools. The analysis of the experimental results shows that the ECPO is a very competitive optimization algorithm.