A comparison of metaheuristics algorithms for combinatorial optimization problems. Application to phase balancing in electric distribution systems

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.