In this paper, a new multi-objective optimization method is proposed to solve large scale structural problems in continuous search space. This method is based on the recently developed algorithm, so called charged system search (CSS), which has been used for single objective optimization. In this study the aim is to develop a multi-objective optimization algorithm with higher convergence rate compared to the other well-known methods to enable to deal with multi-modal optimization problems having many design variables. In this method, the CSS algorithm is utilized as a search engine in combination with clustering and particle regeneration procedures. The proposed method is examined for four mathematical functions and two structural problems, and the results are compared to those of some other state-of-art approaches. © 2013 Elsevier Ltd. All rights reserved.
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