Differential evolution as applied to electromagnetics
In electromagnetics, optimization problems generally require high computational resources
and involve a large number of unknowns. They are usually characterized by non-convex …
and involve a large number of unknowns. They are usually characterized by non-convex …
A competitive mechanism based multi-objective differential evolution algorithm and its application in feature selection
A large number of evolutionary algorithms have been introduced for multi-objective
optimization problems in the past two decades. However, the compromise of convergence …
optimization problems in the past two decades. However, the compromise of convergence …
Fast optimization of electromagnetic design problems using the covariance matrix adaptation evolutionary strategy
MD Gregory, Z Bayraktar… - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
A new method of optimization recently made popular in the evolutionary computation (EC)
community is introduced and applied to several electromagnetics design problems. First, a …
community is introduced and applied to several electromagnetics design problems. First, a …
An efficient approach for optimizing frequency reconfigurable pixel antennas using genetic algorithms
S Song, RD Murch - IEEE Transactions on Antennas and …, 2013 - ieeexplore.ieee.org
In this paper we describe a method for optimizing frequency reconfigurable pixel antennas.
The method utilizes a multi-objective function that is efficiently computed by using only one …
The method utilizes a multi-objective function that is efficiently computed by using only one …
An evolutionary algorithm with constraint relaxation strategy for highly constrained multiobjective optimization
Highly constrained multiobjective optimization problems (HCMOPs) refer to constrained
multiobjective optimization problems (CMOPs) with complex constraints and small feasible …
multiobjective optimization problems (CMOPs) with complex constraints and small feasible …
Automatic fuzzy clustering based on adaptive multi-objective differential evolution for remote sensing imagery
Traditional automatic fuzzy clustering methods can obtain the optimal number of clusters by
maximizing or minimizing one single-objective function using validity indexes. However, the …
maximizing or minimizing one single-objective function using validity indexes. However, the …
Impact of the Zr-substitution on phase composition, structure, magnetic, and microwave properties of the BaM hexaferrite
MA Darwish, HF Abosheiasha, AT Morchenko… - Ceramics …, 2021 - Elsevier
Rapid developments in information technologies and a large rise in electrical and electronic
equipment have generated different forms of electronic environmental contamination …
equipment have generated different forms of electronic environmental contamination …
A multi-objective approach to subarrayed linear antenna arrays design based on memetic differential evolution
In this paper we present a multi-objective optimization approach to subarrayed linear
antenna arrays design. We define this problem as a bi-objective one. We consider two …
antenna arrays design. We define this problem as a bi-objective one. We consider two …
Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
Design of contemporary antenna structures needs to account for several and often
conflicting objectives. These are pertinent to both electrical and field properties of the …
conflicting objectives. These are pertinent to both electrical and field properties of the …
Antenna design using binary differential evolution: Application to discrete-valued design problems
S Goudos - IEEE antennas and propagation magazine, 2017 - ieeexplore.ieee.org
Several antenna design problems are discrete valued. Particle swarm optimization (PSO)
and differential evolution (DE) are popular evolutionary algorithms that have been applied to …
and differential evolution (DE) are popular evolutionary algorithms that have been applied to …