A COMPARISON OF METAHEURISTICS ALGORITHMS FOR COMBINATORIAL OPTIMIZATION PROBLEMS. APPLICATION TO PHASE BALANCING IN ELECTRIC DISTRIBUTION SYSTEMS

• Tipo: Artigo em Revista Científica Internacional
• Data: 2011

Autores

Gustavo Schweickardt (Autor) FEUP; Vladimiro Miranda (Autor) FEUP; G. Wiman (Autor) Outra

Revista

Título: Latin American Applied Research

Vol. 41 Nº 2

Páginas: 113-120

ISSN: 0327-0793

Editora: Planta Piloto de Ingenieria Quimica, CONICET / Universidad Nacional del Sur

Indexação

ISI Web of Knowledge - 5 Citações

ISI Web of Science

Scopus - 7 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia electrotécnica, electrónica e informática

Outras Informações

ID Authenticus: P-002-T15

Abstract (EN): Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multi-objective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 8