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This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA), called PSO-SA, for multi-objective Distribution Feeder Reconfiguration (DFR). The objective functions are to minimize real power losses; deviation of nodes voltage; the number of switching operation and to balance the loads on the feeders. Due to the objectives are different and no commensurable, it is difficult to solve this problem by conventional approaches that optimize a single objective. In the proposed algorithm, these objective functions are first modeled with fuzzy sets to evaluate their imprecise nature and then the hybrid PSO-SA is used to determine the optimal solution. The feasibility of the proposed optimization algorithm is demonstrated and compared with the solutions obtained by other approaches over different distribution test systems. [ABSTRACT FROM AUTHOR]