A comparison of metaheuristics algorithms for combinatorial optimization problems. application to phase balancing in electric distribution systems
Gustavo Alejandro Schweickardt, Vladimiro Miranda, Gustavo Wiman · Americanae (AECID Library) · 2011
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 multiobjective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.