In this paper, a road transportation system in an Iranian province was studied to select the best combination of proposed Projects, within budgetary constraints, by discrete event system simulation. To do this, first, a list of candidate Projects was obtained along with their characteristics. After data collection and analysis, GPSS/H model development and validation, initial transient study, and design of the experimental phases, the developed model was applied to determine the performances of different combinations of candidate Projects under different random conditions. Then, the one with the highest average utilization of the roads was chosen. The results of this paper show that if a suitable set of input data is available for similar transportation systems, then, one can benefit from this simulation study for short and long term planning.

Project portfolio management consists of repetitive cycles of Project evaluation، selection and execution. Project portfolio selection is the main part of Project portfolio management. Organization identifies and prioritizes Projects that are mostly aligned with stated strategic goals while considering real-world restrictions and considerations that are related to scheduling and resource allocation. In this paper، a new comprehensive model for the Project portfolio selection problem over a planning horizon with multiple periods by maximizing profit is developed in which simultaneous selection، scheduling and resource allocation of Projects are considered. The model incorporates Project interdependency and strategies of Project divisibility، reinvestment، external investment and resourcing in different ways at the same time in choosing the best execution schedule for the Projects in real-life applications. In addition، resource and budget constraints، cardinality restriction، precedence relationship and scheduling، setup and resource costs are included in the model. Numerical examples under eight scenarios are presented to highlight the characteristics of the proposed model.

A vast number of organizational Projects as well as complexity of decision making process can cause particular challenges for Project management and its leadership. In order to use organization assets and opportunities efficiently, it is necessary that manager implement a comprehensive multidimensional Project portfolio management system that considers economic, social and technical details of the Projects. Resource constraint compels managers to select operational proposal Projects. Thus managers can maximize organizational utility due to Project portfolio’s resource constraint. This study considers the interactive effects of Project portfolio evaluation and sharing organizational Project resources with respect to its evaluation and choice of the Projects. In this two-step model, first a branch and bound algorithm with resource interaction was utilized to screen maximal portfolio and, in the next step, each portfolio was evaluated based on artificial neural networks to rank the end Project portfolios. Also, the ANN scores are strongly correlated with the DEA and COLS efficiency scores.

Selecting an effective Project plan is a significant area in the Project management. The present paper introduces a technique to identify the Project plan efficient frontier for assessing the alternative Project plans and selecting the best plan. The efficient frontier includes two criteria: the Project cost and the Project time. Besides, the paper presents a scheme to incorporate Directed Acyclic Graph (DAG) into the Project risk analysis.This scheme is used to estimate the expected impacts of the occurrence of the Project risks on the Project cost and the Project time. Also, a theoretical model is defined to provide integration between Project risk analysis and overall Project planning using the breakdown structures. We believe that applying the proposed technique helps the company's managers in most effective manner dealing with his complicated Project plan assessment and selection problems. The application of the technique was implemented in the companies in construction industry in which represented a considerable cost and time improvements.

Choosing the appropriate Project requires good planning based on scientific foundations, especially in Iraq, due to the tremendous development witnessed in the construction industry. Incorrect selection of Projects leads to many challenges that may accompany the Project throughout its implementation period such as delay in delivery, exceeding the planned cost, overlapping work, and finally, Project stopping. In Iraq, focusing on contractor selection, specifically who submits the lowest bid, regardless of the actual feasibility of the Project and the integration of its components, led to the spread of random Projects that do not achieve their true purpose due to neglect of integration. The following steps were followed to overcome the mentioned problems: (1) Thirty-one influence factors on choosing the appropriate Project were identified through an extensive review of the literature; (2) Only seven factors were selected according to the Fuzzy Delphi Technique (FDT); (3) The priority and weight of each factor were determined through pairwise comparisons using the Analytical Network Process (ANP). As a result, a model was developed to select the most appropriate Project, and to verify the validity of the proposed model, a case study was applied to three Projects for constructing residential complexes belonging to the private sector, which can give an excellent view of the efficiency of the basic Project elements, which are structural/organizational, technical, and financial aspects in selecting the best Project.

Project selection is considered as an important problem in Project management. It is multi-criteria in nature and is based on various quantitative and qualitative factors. The main purpose of this paper is to present a new rank-based method for Project selection in outranking relation. According to this approach, decision alternatives were clustered in the concordance matrix and the discordance matrix through the ELECTRE model based on intuitionistic trapezoidal fuzzy numbers. Then, the two matrices were integrated and ranked using grey relational coefficients and the Minkowski space distance. The results of the model were compared with grey relational Projection method with intuitionistic trapezoidal fuzzy number. To illustrate the proposed methodology, a case study was conducted to select National Iranian Oil Company Projects.