The imperialist competitive algorithm (ICA) is developed based on the socio-political process of imperialist competitions. It is an efficient approach for single-objective optimization problems. However, this algorithm fails to optimize multi-objective problems (MPOs) with conflicting objectives. This paper presents a modification of the ICA to different multi-objective problems. To improve the algorithm performance and adapt to the characteristics of MOPs, the Sigma method was used to establish the initial empires, the weighted sum approach (WSum) was employed for empire competition, and an adaptive elimination approach was used for external archiving strategy. the results indicated that the suggested algorithm had a higher performance compared to other algorithms based on diversity and convergence characteristics.