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The problem of handling equipment selection plays a significant role in the total cost of a mining project; so that it can affect the activity and continuity of the project and is a strategic problem. In this study, an integrated model based on two fuzzy multi-criteria decision making techniques for handling equipment selection is proposed. The proposed evaluation model is derived from group decision making, fuzzy set theory, analytical hierarchy process (AHP), and Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The fuzzy AHP (FAHP) method is utilized to calculate the relative importance of the evaluation criteria, then, fuzzy TOPSIS (FTOPSIS) is applied for evaluating the feasible handling equipment in order to select the best handling system among a pool of the possible alternatives. The model is applied for a real world case study to demonstrate the capability and effectiveness of the proposed model. To investigate the result sensitiveness to the changes of the criteria weights, a sensitivity analysis is finally conducted. [ABSTRACT FROM AUTHOR]

The complexity and dynamics of the executive projects have coped contractors with substantial hazards and losses. Project risk management is a critical tool for authority to improve its performance and secure the success of the organization. However, a number of standards and approaches have been developed to formulate the projects based on their risks. The Elena guideline is a systematic standard developed by Iran Project Management Association. This guideline provides the full cycle of the risk management process. Risk evaluation is the key part of the risk management process. On the other hand, different techniques have been developed to model a risk evaluation problem. Fuzzy inference system is one of the most popular techniques that is capable of handling all types of the uncertainty involved in projects. This paper proposes a three-stage approach based on the fuzzy inference system under the environment of the Elena guideline to cope with the risky projects. Finally, an illustrative example of the risk evaluation is presented to demonstrate the potential application of the proposed model. The results show that the proposed model evaluates the risky projects efficiently and effectively. [ABSTRACT FROM AUTHOR]

Nanotechnology plays a significant role in construction industry. The construction industry has been employed nanomaterials to improve the performance of construction components and the safety of the structure and to reduce the energy consuming and the cost of maintenance. In other words, nanotechnology has a substantial impact on the construction industry. Therefore, it is necessary to identify and evaluate the critical factors of the application of nanotechnology in construction in order to concentrate on the most critical factors. However, several techniques have been developed to prioritize the evaluation criteria. Analytical network process (ANP) technique, a branch of multi criteria decision making (MCDM) methods, is a powerful tool to rank a limited number of criteria. This technique takes into account both tangible and intangible criteria in the process of formulation of a decision making problem. This method is capable of handling all types of independence and dependence relationships. On the other hand, intuitionistic fuzzy set (IFS) is a well-known technique in considering the inherent uncertainty involved in the process of modelling a decision making problem. In this paper, a new model based on the IFS and ANP technique is proposed to evaluate the critical factors of the application of nanotechnology in the construction industry. The results demonstrate that the proposed model has a high potential for taking into account the uncertainty in the form of a three dimension function, including membership, non-membership, and non-determinacy. [ABSTRACT FROM AUTHOR]