To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning (ERP) implementation, combined with program evaluation and review tech-nique (PERT), some optimization models are proposed, which include the implementation schedule model, the time-cost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm (GA) based on stochastic simulation technique is introduced to the optimiza-tion models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation. To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning (ERP) implementation, combined with program evaluation and review tech-nique (PERT), some optimization models are proposed, which include the implementation time-cost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm (GA) based on stochastic simulation technique is introduced to the optimiza-tion models Finally, an example is presented to show that the models and algorithms are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.