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In this paper, an efficient Tribe-Modified Shuffled Frog Leaping Algorithm (T-MSFLA) is presented to solve Multi-objective Distribution Feeder Reconfiguration (MDFR) problem with regard to Distributed Generator (DG) units. The Distribution Feeder Reconfiguration (DFR) is one of the most important control schemes in the distribution networks, which can be affected by DG units. The main focus of this study is to minimize the real power loss, deviation of the nodes' voltage, and emission produced by DG units and distribution companies (substation buses), and total cost of the active power generated by DG units and distribution companies, so that radiality of the network is maintained. In this paper, the max-min method has been used to preserve the radiality of network. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective problem. This paper presents a new T-MSFLA algorithm for the MDFR problem. In the proposed algorithm (T-MSFLA) at first we modify the frog leaping rule of shuffled frog leaping algorithm, the modified algorithm is MSFLA, and then a Tribe-MSFLA is used to prevent the prematurity of MSFLA. We consider an external repository to save non-dominated solutions found during the search process. Since the objective functions are not the same, a fuzzy clustering technique is used to control the size of the repository within the limits. The proposed algorithm is tested on three distribution test feeders. The results of simulation show that the proposed method is very powerful and guarantees to obtain the global optimization.