Implementing Taguchi and cuckoo search to optimize LAA

Abstract

This paper presents a global optimization technique named as Taguchi's method (TM) and an evolutionary natured-inspired metaheuristic cuckoo search (CS) optimization method and applied to linear antenna array (LAA) designed for minimum side lobe levels and nulls at the desired directions. TM was developed on the basis of the orthogonal array (OA) concept, which offers systematic and efficient characteristics which effectively reduces the number of tests required in an optimization process. Another nature-inspired evolutionary CS optimization algorithm is implemented which is capable of solving general N-dimensional, linear and nonlinear optimization problems. The Levy flight concept of CS optimization method shows its random walk which helps to generate new solutions randomly. The array geometry synthesis is first formulated as an optimization problem with the goal of side lobe level (SLL) suppression and null prescribed placement in certain directions, and then solved by both TM and CS method. Obtained results show that the TM has the tremendous ability to converge quickly.