Publication detail

Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence

ŠEDĚNKA, V. RAIDA, Z.

Original Title

Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence

English Title

Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence

Type

journal article in Web of Science

Language

en

Original Abstract

The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM). The hit rate and the quality of the Pareto front distribution are classified.

English abstract

The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO). The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM). The hit rate and the quality of the Pareto front distribution are classified.

Keywords

Multi-objective optimization, binary genetic algorithm, particle swarm optimization, Pareto front, finite element method.

RIV year

2010

Released

01.09.2010

Publisher

SPOLECNOST PRO RADIOELEKTRONICKE INZENYRSTVI, CZECH TECHNICAL UNIVERSITY, DEPT OF ELECTROMAGNETIC FIELD

Location

TECHNICKA 2, PRAHA, CZ-16627, CZECH REPUBLIC

Pages from

369

Pages to

377

Pages count

9

BibTex


@article{BUT49757,
  author="Vladimír {Šeděnka} and Zbyněk {Raida}",
  title="Critical Comparison of Multi-objective Optimization Methods: Genetic Algorithms versus Swarm Intelligence",
  annote="The paper deals with efficiency comparison of two global evolutionary optimization methods implemented in MATLAB. Attention is turned to an elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel multi-objective Particle Swarm Optimization (PSO).
The performance of optimizers is compared on three different test functions and on a cavity resonator synthesis. The microwave resonator is modeled using the Finite Element Method (FEM). The hit rate and the quality of the Pareto front distribution are classified.",
  address="SPOLECNOST PRO RADIOELEKTRONICKE INZENYRSTVI, CZECH TECHNICAL UNIVERSITY, DEPT OF ELECTROMAGNETIC FIELD",
  chapter="49757",
  institution="SPOLECNOST PRO RADIOELEKTRONICKE INZENYRSTVI, CZECH TECHNICAL UNIVERSITY, DEPT OF ELECTROMAGNETIC FIELD",
  journal="Radioengineering",
  number="3",
  volume="19",
  year="2010",
  month="september",
  pages="369--377",
  publisher="SPOLECNOST PRO RADIOELEKTRONICKE INZENYRSTVI, CZECH TECHNICAL UNIVERSITY, DEPT OF ELECTROMAGNETIC FIELD",
  type="journal article in Web of Science"
}