چكيده به لاتين
In dynamic environments such as projects environment, even usual projects with simple structures have their own complexities. On the other hand, recent advances in technology and fundamental changes in most scientific areas have affected projects and made their nature and environmental circumstances much more complex than in the past. With the increase in complexity, the amount of information needed to control and manage the project increases. Expressly recognized that the complexity has an impact on project performance and ultimately will affect on project success. In general, the increasing complexity of projects is a growing source of project risks. One of the main steps to manage and control a system complexity is to evaluate and measure its complexity. Since we cannot properly manage anything that cannot be measured. Hence, proposing a solution to evaluate and analyze the project complexity is one of the objectives of this research. Furthermore, one of the other main factors for a project’s success is the assignment of an appropriate project manager. The amount and type of project complexity have been explained as influential factors for determining the competent project manager. However, a specific approach for project manager selection considering the project complexity is not provided yet. Because of the ambiguity and uncertainty of complexity context, the subjective nature of competency evaluation and the difficulty of the exact quantification of complexity and competency values based on available information, the application of fuzziness could be very appropriate. Therefore, in this study we try to design and implement an inference system and a group decision-making approach in fuzzy environment to evaluate project complexity and select the best project manager taking into account the project complexity. Owing to the importance of construction projects in the development of countries' basic infrastructures and their extensive scope, we exclusively studied this kind of projects. In addition, it should be noted that from the viewpoint of complexity theory, system complexity can exist in two forms: static and dynamic. Accordingly, considering the breadth of issues related to each of these two complexity areas, just the static complexity of construction projects has been studied here. Finally, in order to test the validity of the proposed approach, the data about several power plant projects was collected and the behavior of model was assessed based on this real data.
