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Risk management project is an important aspect of general project risk element transmission theory. Traditional network planning technology encountered great obstacles in project risk management issues, and often unable to accurately forecast the risk, resulting great loss of costs. To address the cost-time optimization problem considering the risk elements, this paper established a network planning risk element model, which divides risk elements into discrete model and continuous model to be discussed separately. In the discrete model costs and risk element matrix is introduced to get the corresponding programming model; In Continuous model the idea of machine learning model is used to minimum the desired risk. Based on this model, by using genetic algorithm's efficient and rapid global search capability, this paper improves the genetic algorithm developed by Feng and others, increases the risk elements and eventually gets the cost-time curve considering risk elements. This effectively solves the network planning cost optimization problem.