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A major challenge to the transmission system planning problem in the emerging electricity market environment is that more uncertain factors have to be resolved. Although the transmission system optimal planning problem has been extensively studied for several decades, available standard optimization models and methods could not well solve this problem for the competitive electricity market environment. Given this background, a new methodological framework for optimal transmission system expansion planning in a competitive electricity market environment is presented in this paper with several uncertainty factors such as the locations and capacities of new power plants as well as demand growth well taken into account. A stochastic optimization model is first formulated under the presumption that the locations and capacities of new power plants together with future load demand could be modeled as specified probability distributions. An approach is then presented for solving the optimization problem based on the Monte Carlo simulation method and the genetic algorithm. Finally, a numerical example is given to illustrate the essential features of the proposed method.