Sidelobe-Level Suppression for Circular Antenna Array via New Hybrid Optimization Algorithm Based on Antlion and Grasshopper Optimization Algorithms

Abstract

The suppression of the side-lobe level (SLL) of antenna arrays is a significant factor that can enhance the reliability and validity of a communication system. Recently, metaheuristic algorithms have been widely implemented in the design of antenna arrays, in order to find the optimal minimization for the side-lobe level of the array's radiation pattern. In this paper, we propose a new hybrid algorithm that combines the characteristics of two stochastic algorithms, Antlion Optimization (ALO) algorithm and Grasshopper Optimization Algorithm (GOA). ALO, which is an evolutionary algorithm, is robust in exploitation and has been effectively used in many articles in the literature. GOA has strong capability of exploration all over the search space due to the swarm nature of the algorithm, which has been proven in several articles in the literature. Therefore, combining these characteristics and overcoming the drawbacks of ALO and GOA are the main motivation behind hybridizing ALO and GOA in one hybrid algorithm. Simulation results show that the proposed hybrid algorithm has a good performance in the radiation pattern optimization of circular antenna array (CAA) and fast convergence rate compared with other strong optimization algorithms, which prove the efficiency, robustness, and stability of the hybrid algorithm.

Circular Antenna Array Synthesis Using Multiverse Optimizer

“…e obtained results from both MVO and MMVO were comprehensively compared with the results of ten different algorithms which are GA [14], PSO [15], FA [16], SQP [13], SADE [13], HA [12], ALO [12], BBO [13], SOA [17], and SA [18]. During the optimization, the following fitness function was used:…”

“…Synthesis process was applied for CAAs with 8, 10, 12, and 20 elements. e obtained results were compared with the results of ten different optimization algorithms: hybrid algorithm (HA) [12] based on Antlion Optimization (ALO) and Grasshopper Optimization Algorithm (GOA), ALO [12], Sequential Quadratic Programming (SQP) [13], Self-Adaptive Differential Evolution (SADE) [13], Biogeography Based Optimization (BBO) [13], GA [14], PSO [15], Firefly Algorithm (FA) [16], Seeker Optimization Algorithm (SOA) [17], and Simulated Annealing (SA) [18].…”

The optimal synthesis of scanned linear antenna arrays

“…Furthermore, the intensity of search agents in the proposed method has been reduced rapidly compared with ALO and GOA, due to the modification of c parameter and its combination with other shrinking factors. Thus, the hybrid method guarantees the mature and fast convergence compared with ALO and GOA [22].…”

“…In [20][21][22], we proposed a new hybrid method that combines the features of two metaheuristic algorithms; Grasshopper Optimization Algorithm (GOA) [19] and Antlion Optimization (ALO) algorithm [18]. ALO is robust in exploitation process, which has been proved in many papers in the literature like [23,24].…”

“…where defines the next position for ℎ grasshopper and ℎ dimension, and are the upper and lower bounds in the d th dimension, respectively, and ( ) = − − − where f represents the intensity of attraction force and l indicates the attractive length scale [22].…”