A Multi-objective Memetic Optimization Ap- Proach to the Circular Antenna Array De- Sign Problem

The paper provides a novel approach to the design of nonuniform planar circular antenna arrays for achieving maximal side lobe level suppression and directivity. The current excitation amplitudes and phase perturbations of the array elements are determined using an Adaptive Memetic algorithm resulting from a synergy of Differential Evolution (DE) and Learning Automata that is able to significantly outperform existing state-of-the-art approaches to the design problem. Moreover, existing literature considers the design problem as a singleobjective optimization task that is formulated as a linear sum of all the performance metrics. Due to the conflicting nature of the various design objectives, improvements in a certain design measure causes deterioration of the other measures. Following this observation, the single-objective design problem is reformulated as a constrained multi-objective optimization task. The proposed memetic algorithm is extended to the multi-objective framework to generate a set of non-dominated solutions from which the best compromising solution is selected employing a fuzzy membership based approach. An instantiation of the design problem clearly depicts that the multiobjective approach provides simultaneous side lobe level suppression and directivity maximization in comparison to the single-objective scenario. Received 27 April 2012, Accepted 23 July 2012, Scheduled 25 July 2012 * Corresponding author: Abhronil Sengupta ([email protected]).