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A modified tabu search method for global optimizations of inverse problems is presented. In the proposed algorithm, the whole search procedure is divided into three different phases: intensification, diversification, and refinement. Two “new point generating mechanisms” as well as a “dynamic parameters updating” rule are proposed to improve the searching efficiency without compromising the solution's accuracy. Numerical results on TEAM Workshop Problems 22 and 25 are used to demonstrate the effectiveness and advantages of the proposed method.