[PDF] Top 20 The Multi-Objective Optimization of Non-Uniform Linear Phased Arrays Using the Genetic Algorithm

... by using two different ...amplitude-only optimization [10, 14, ...with uniform excitations, resulting in a non- uniform array geometry [7, 16, ...by optimization algorithms to ... See full document

... others. Optimization of composite laminates with respect to ply angels to maximize the strength is necessary to realize the full potential of fiber reinforced ...modified Non- Dominated sorting ... See full document

... Deb, K. (2000). An efficient constraint handling method for genetic algorithms. Com puter m ethods in app lied mechanics an d engineering, 186, 311-338. Deb, K. (2001). Multi-objective ... See full document

... use optimization were ...current multi-objective optimization knowledge was identified in the selection operator research and two research questions were posed to further explore this ... See full document

... solve multi-variant ...EWR. Genetic algorithms (GA) and artificial neural networks (ANN) are popular software technologies used for the optimization of machining ...by using back-propagation ... See full document

... for linear arrays: the time modulation, the non- uniform excitation [21, 22] and the phase-position method [23] using MOEA/D-DE to achieve the design objectives in each ...single ... See full document

... the multi-objective optimization problem in which it is objectives to find values of the design variables so that difference of same behaviors and their expected values achieves it’s the minimum ... See full document

... A multi-objective uniform-diversity genetic algorithm (MUGA) has been proposed and successfully used to optimally design linear state feedback controllers from a ... See full document

... IEEE Institute of electrical and electronics engineer MOEA Multi-objective evolutionary algorithm MOP Multi-objective optimization problem NSGA-II Non-dominated sorting genetic algorithm[r] ... See full document

... for multi-objective optimization problems: such as Ant Colony algorithm, COA (Cuckoo Algorithm, Genetic algorithm, particle swarm optimization algorithm, ... See full document

... Many optimization problems in engineering are usually multiple objectives that their Pareto-optimal solutions are a set of optima instead of a single optimal solution and usually, there is no any best ...many ... See full document

... of multi-objective optimization in economics Pareto ...of objective functions in multi-objective optimization problems (MOPs) stands for a set of solutions that are ... See full document

... present non linear multi objective problem can be effectively solved using evolutionary techniques such as Genetic ...of genetic algorithms, their operation and various ... See full document

... the multi-objective ...each objective function. The overall objective function is the linear weighted ...use Genetic Algorithm to solve ... See full document

... large arrays is space tapering ...or non uniform spacing of the elements. Non uniformly spaced elements generate a low-sidelobe amplitude taper by placing equally weighted elements in such a ... See full document

... points. Multi-objective genetic algorithm with Pareto rank approach can be used to increase the K-means ...of non-dominated solution; in this research it consists of a pair of values ... See full document

... In this paper, a well-known three bar truss design model is considered as a Structural design model. The results are compared numerically with both in fuzzyoptimization technique and intuitionistic fuzzy ... See full document

... The rest of the paper is arranged as follows: Section 2 is preliminaries to intuitionistic fuzzy set and intuitionistic fuzzy numbers needed for consequent sections. Section 3 comprise of modelling of an intuitionistic ... See full document

... in objective function space in multi-objective problems is based on responses that are not superior than ...all objective functions because at least an objective function gets ...these ... See full document

... paper, Non Linear Integer programming model is designed, the optimal scheduling decision for each power flow is obtained by Lagrangian dual which minimizes the power flow route ... See full document