Benchmark Antenna Problems for Evolutionary Optimization Algorithms

Abstract

Abstract-A set of antenna-optimization problems is presented that satisfies the necessary requirements to form a test suite useful for measuring and comparing the performance of different evolutionary optimization algorithms (EAs) when they are applied to solve complex electromagnetic problems. The ability of the proposed test suite to find strong and weak points of any EA is illustrated by a complete study of four broadly used evolutionary algorithms carried out with the aid of the new test functions.

Application of the Invasive Weed Optimization Technique for Antenna Configurations

“…The reason of this selection has been explained with details in [13]. These configurations have been optimized there with other optimization techniques like GA and PSO.…”

“…IWO parameters which are used for optimization of configuration 4 are Figure 10. Collinear array of N half-wavelength dipoles [13]. shown in Table 4.…”

Optimization of Antenna Configuration With a Fitness-Adaptive Differential Evolution Algorithm

“…However, if the agent moves away from the optima, then it is more perturbed and during DE-type crossover, the offspring inherits lesser genetic information from the parent, so that the agent may be able to explore alternate regions quickly. In this paper, the proposed algorithm FiADE has been used to optimize certain electromagnetic antenna configurations in a recently proposed [24] electromagnetic benchmark test-suite. The reason for selecting particularly these problems has been dealt in details in [24].…”

“…In this paper, the proposed algorithm FiADE has been used to optimize certain electromagnetic antenna configurations in a recently proposed [24] electromagnetic benchmark test-suite. The reason for selecting particularly these problems has been dealt in details in [24]. Though, all the antenna configurations involve thin wire antenna geometries just for ease in simulating purpose, but as the complexity of the equations involved in these problems is quite similar to that of other computational electromagnetic problems, the utility of the proposed test cases goes beyond the thin-wire antenna design to the optimization of arbitrary electromagnetic problems in general.…”

Accelerated Antenna Design Methodology Exploiting Parameterized Cauchy Models

“…Many interesting optimization approaches have been proposed, and some have already become a standard feature in many commercial electromagnetic simulators [1]. Among these are the classical quasi-Newton techniques [2], genetic-based algorithms [3,4], particle swarm optimization [5][6][7], evolutionary programming [8][9][10], and space mapping [11][12][13][14][15]. Some of these algorithms are also integrated with artificial neural networks [16,17] leading to an efficient design approach.…”