In this paper, a particle swarm optimization (PSO) technique is proposed for solution of the generation expansion planning (GEP) problem in a competitive electricity market. GEP is one of the important decision-making activities in electric utilities and acquires a principle role in the deregulated environment for electricity trading. It is highly constrained non-linear dynamic optimization problem that can only be fully solved by complete enumeration and is computationally impossible for a real world GEP problem. The utility has to take both independent power producers participation and environment impact (CO2 emission) with satisfying all electrical and energy market constraints simultaneously. The proposed PSO based method has a strong ability to find most optimistic results and is robust for solution problem featuring non-linearity, non-differentiability and high-dimensionality. The proposed method is compared with a GA based technique to illustrate its robust performance considering different purchase prices for IPPs and CO2 emission limits. Analysis reveals that the proposed approach is an inherent, effective and economical tool for the solution of the competitive GEP problem that is easy to implement and is also superior to the GA based technique. (C) 2009 Elsevier Ltd. All rights reserved.