Phased Antenna Array Design using Shuffled Frog-Leaping Algorithm

In this paper, we present a new meta-heuristic approach (memetic algorithm) to address multi-objective problems in planar phased arrays. Memetic algorithms are hybrid algorithms that combine the benefits of a global search evolutionary algorithm with a local search method. The Shuffled Frog-Leaping Algorithm (SFLA) consists of a virtual population of frogs partitioned into different memeplexes. It performs a memetic evolution within the memeplex (local search) and a shuffling mix process between memeplexes (global search) to deliver optimum solutions in optimization problems. Derived results show improved characteristics of the antenna array.