Nonuniform antenna array design by parallelizing three-parent crossover genetic algorithm

Abstract

Antenna plays a very important role in wireless communication. Array elements laid out nonuniformly could achieve better frequency reliability and lower sidelobe level than uniform spaced elements. Designing desirable nonuniform antenna array requires the tuning of distances between each element, excitation, amplitude, and so on. Such design problem can be solved by genetic algorithm. Based on a recently genetic algorithm modification, this paper attempts to invent a parallel framework to enhance the efficiency of genetic algorithm. The parallel framework increases exploitation search of genetic algorithm. The effectiveness of the proposed algorithm is firstly demonstrated on toy problems with different kinds of problem complexity. The proposed algorithm is then verified on nonuniform antenna array design. Compared with genetic algorithm without parallelization, the novel algorithm attains better design solution and saves a lot computation time.

A New Lagrangian Problem Crossover—A Systematic Review and Meta-Analysis of Crossover Standards

“…In the elucidation example, Figure 8 highlights the problems involved in calculating future generations based on deliberate offspring generated by swapping genes according to the general pseudocode. Three-Parent Crossover (TPX) [57]: According to the prior solution approach, in this kind of operator, there are numerous probability rate algorithms with which to create innovative offspring from three parent genes. In the elucidation example, Figure 8 highlights the problems involved in calculating future generations based on deliberate offspring generated by swapping genes according to the general pseudocode.…”

“…As shown in Figure 9, two genes were crossed and real numbers were swapped between them, resulting in two new offspring. [57]: This standard should be derived from a single genome (𝑘), randomly chosen from both chromosomes (𝑛). For instance, in Figure 10, 𝑘 = 2 and then we define a random parameter (α = 0.5).…”

“…We modify the kth gene of chromosome 1 and chromosome 2 to generate offspring by the selected asthmatic formula that is calculated as Equation (1) [60,61]. Single arithmetic crossover (SAX) [57]: This standard should be derived from a single genome (k), randomly chosen from both chromosomes (n). For instance, in Figure 10, k = 2 and then we define a random parameter (α = 0.5).…”