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

• Type: Article in International Scientific Journal
• Date: 2011

Authors

Gustavo Schweickardt (Author) FEUP; Vladimiro Miranda (Author) FEUP; G. Wiman (Author) Other

Journal

Title: Latin American Applied Research

Vol. 41 No. 2

Pages: 113-120

ISSN: 0327-0793

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

Indexing

ISI Web of Knowledge - 5 Citations

ISI Web of Science

Scopus - 7 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8