عنصر خطر تحقیقات تئوری انتقال چند هدفه خطر-زمان-هزینه تجارت کردن

Risk management project is an important aspect of general project risk element transmission theory. To solve the multi-objective time-cost trade-off problem considering the risk elements effectively, this paper establishes an analytical model for multi-objective risk-time-cost trade-off problem based on general project risk element transmission theory. We divide risk elements into discrete model and continuous model to be discussed separately, and the two models for multi-objective risk-time-cost trade-off problem are established by taking Markov dynamic PERT network into classical PERT network. Thus, we combine Radial Basis Function (RBF) neural network to solve the discrete model of the problem. Finally, a practical example illustrates the effectiveness of the algorithm.

The time-cost trade-off problem (TCTP) is the most important content in the project management. Although many scholars did a lot of research on the problem and got many achievements, the TCTP considering the risk elements has not been solved effectively. In the TCTP, the objective is to determine the duration of each activity in order to achieve the minimum total costs of the project. Studies on TCTP have been done using various kinds of cost functions such as linear [1] and [2], discrete [3], convex [4] and [5], and concave [6] and so on. From the above we can see, they all concerned the complex time planning, but comparing with the real situation, there are two main problems. First, there are no model considering the risk elements on TCTP; Second, how to get the optimization about the risk-time-cost when the network is random. In order to resolve the above problems, this paper improved the model in the paper [9] based on the general project risk element transmission theory [7] and [8] and get the multi-objective risk-time-cost trade-off problem(MRTCTP) model when risk elements considering in dynamic PERT network. Thus, this paper gets the relationship of the resource allocation and the risk elements by combining the RBF neural networks and putting the multi-objective risk-time-cost programming problem into the multi-objective cost, expectation, variance, risk-time probability programming. The paper is organized as follows. Section 2 presents the analytical model of the multi-objective risk-time-cost trade-off problem (MRTCTP), and gives the definition of the Markov dynamic PERT network. Section 3 presents the neural network analytical algorithm of MRTCTP. An empirical example is presented in Section 4. Finally, Section 5 concludes the paper.

Based on the general project risk element transmission theory, this paper analyzes the multi-objective risk-time-cost trade-off problem by introducing the risk element, it improves the Markov dynamic PERT model, and finally get the analytical model of multi-objective risk-time-cost trade-off problem. By introducing neural network, and making an effective solution of the model, the effectiveness of the approach is illustrated with a practical example. By establishing the multi-objective risk-time-cost trade-off problem model, it not only has an important effect on the risk element transmission theory, but has an important significance for actual project. If we applied the model to the field of computers, the reliability model of computer network considering risk elements can be built. This should be a subject of future research and we expect further improvement of the risk element transmission theory.