In this paper, order reduction of power system model using Particle Swarm Optimization (PSO) and Differential Evolution (DE) based on different objectives is considered. In the literature, model reduction problems using soft computing techniques are solved based on only by the minimization of Integral square error (ISE) where large errors between original and reduced order are magnified. But there are other performance indices like Integral absolute error (IAE), Integral time absolute error (ITAE) etc. where IAE gives equal weights to both small and large errors and ITAE puts a heavy penalty on errors that persist for long period of time. Model reductions using PSO and DE are solved based on single ISE, IAE and ITAE objectives for numerator. The denominator is reduced by dominant pole retention method. The proposed method is  applied to the transfer function matrix of a 10^th order two-input two-output linear time invariant model of a power system. The performance of the algorithms is tested by comparing the relevant simulation results.