Measuring actual project progress and comparing it with the planned time schedule is essential in controlling of a project. The outcome of the latter follows the s-curve diagram, which compares actual progress with the planned amount and finally analyzing any gap between them to draw directions for project scheduling. However, final duration of the project cannot be either estimated or predicted through conventional methods. The new method, using Rules of kinematics, can calculate the final duration of the project. This novel approach is successfully implemented on a construction project. The first objective in new method is forecasting final duration of the project, finding equation path and draw a new s-curve diagram for actual status during the execution process. The second objective is to evaluate schedule performance of the project and report the status of the project at each period which is a useful tool for managers.

In construction cost management system, normally earned value management (EVM) is applied as an efficient control approach in both status detection and estimation at completion (EAC) cost forecasting. The traditional approaches in EAC predictions normally extend the current situation of a project to the future by employing pervious performance factor. The proposed approach of this paper considers both qualitative and quantitative factors affecting the EAC prediction. The proposed approach of this research not only estimates the completion of the project, but also it can generate accurate forecast for the entire future periods using a fuzzy neural network model. The model is also implemented for a real-world case study and yields encouraging preliminary results.

Nowadays, projects have become so widespread in the world that individuals and organizations are always involved in a variety of them. Recent advances in technology and fundamental chang-es in most scientific disciplines have had an essential impact on projects, and have made the na-ture and environmental conditions governing them to become more complex than before. With increasing complexity, the amount of information needed for project management increases. In general, the increasing complexity of projects is a growing source of project risks. It has been recognized that complexity affects the performance of a project and will be effective in its suc-cess. In this context, the traditional principles and practices of project management are no longer able to control the emerging complexity of projects. In addition, one of the key factors for the success of the projects is the appropriateness of the project manager's assignment. Many studies have been carried out in identifying the suitability criteria of the project manager and the methods of selecting the project manager. In most of these studies, the amount and type of complexity of the project are mentioned as factors influencing the design of an appropriate project manager. However, there has not yet been a specific approach for selecting the project manager with re-gard to the complexity of the project. Therefore, in this research, we try to investigate the rela-tionship between the complexity of the project and the merits of the project manager by applying a structural equation modeling approach.

This paper presents a systematic approach for evaluating the performance of a project based organization using a two level fuzzy data envelopment analysis (DEA) technique in project based organizations. In order to determine the required inputs and outputs, important indicators are selected using both expert judgments and statistical analysis and a two-level DEA model is adapted. In this model, by considering different inputs and outputs through a hierarchical process, a large number of sub indicators are provided and rolled up to a higher level. Since inputs and outputs are combinations of qualitative and quantitative indicators, fuzzy logic is also included through the modeling procedure. In addition, since the exact amount cannot be attributed to the indicators, the proposed model uses interval values for the project life cycle. Finally, some of the projects are evaluated throughout the approach proposed in this paper.

Earned Value Management (EVM) has been a well-known methodology used since the 1960s when the US department of defense proposed a standard method to measure project performance. This system relies on a set of often straightforward metrics to measure and evaluate the general health of a project. These metrics serve as early warning signals to timely detect project problems, or to exploit project opportunities. A key aspect of EVM is to estimate the completion cost of a project by considering both cost and schedule performance indices. However, good performance of cost and schedule performance indices does not necessarily guarantee cost effectiveness of the project regardless of the overhead costs. The reason is because, in most project-based organizations, overhead costs constitute a significant proportion of the total costs. However, EVM indices are usually calculated in the absence of the so-called overhead costs. This paper, first, seeks to remedy this problem by proposing a practical procedure of allocating overhead costs in project-based organizations. Then the traditional EVM indices are revised by consider-ing the allocated overhead costs. Finally, a case study demonstrates the applicability of the proposed method for a real-life project.