Time-Cost-Quality Trade-off Optimization Of Project Under Uncertain Environment

In recent years, with the rapid development of national economy, the scale and complexity of project are on the increase. Time, cost and quality are the main goals of project management. They directly affect the completion of the whole project. Because of the unity of opposites relationship of the three goals, it is difficult to reach the best state of them at the same time. Therefore, the important problem of project management is to achieve a trade-off optimization of these three goals. Furthermore, the uncertain factors have a great influence on project in the process of project implementation. However, the traditional optimization methods can not describe uncertain factors completely.Based on uncertain programming, this thesis studies the multi-objective optimization problem of project management under uncertain environment, and builds the uncertainty expected value model of multi-mode time-cost-quality trade-off optimization and the uncertainty chance-constrained model of linear time-cost-quality trade-off optimization. The major works of this thesis are as follows.(1) It studies project trade-off optimization problem of multi-mode under uncertain environment. Firstly, the time, cost and quality are described by uncertain variables in different modes, and the uncertainty distributions of time, cost and quality are obtained by experts’ experimental data. Based on uncertain programming, an uncertain expected value model of multi-mode time-cost-quality trade-off optimization is built. Secondly, a hybrid intelligent algorithm integrating genetic algorithm and particle swarm optimization algorithm is designed for solving the model. Finally, an example is provided to illustrate the practicability and effectiveness of the model.(2) It studies uncertain trade-off optimization problem of linear time-cost-quality. Firstly, it analyzes the relationship among time, cost and quality, and builds the time-cost linear equation and the time-quality linear equation. Secondly, based on the time-cost linear equation and the time-quality linear equation, an uncertain chance-constrained model is built, and an intelligent algorithm is designed for solving the model. Finally, an example is provided to illustrate the effectiveness of the model.The models of this thesis can solve some problems of project management underuncertain environment. The results of this thesis may provide some help for project decision makers.