Process of handling equipment selection is one of the most important and basic parts in the project planning, particularly mining projects due to holding a high charge of the total project & apos; s cost. Different criteria impact on the handling equipment selection, while these criteria often are in conflicting with each other. Therefore, the process of handling equipment selection is a complex and multi criteria decision making problem. There are a variety of methods for selecting the most appropriate equipment among a set of alternatives. Likewise, according to the sophisticated structure of the problem, imprecise data, less of information, and inherent uncertainty, the usage of the fuzzy sets can be useful. In this study a new integrated model based on fuzzy analytic hierarchy process (FAHP) and fuzzy technique for order preference by similarity to ideal solution (FTOPSIS) is proposed, which uses group decision making to reduce individual errors. In order to calculate the weights of the evaluation criteria, FAHP is utilized in the process of handling equipment selection, and then these weights are inserted to the FTOPSIS computations to select the most appropriate handling system among a pool of alternatives. The results of this study demonstrate the potential application and effectiveness of the proposed model, which can be applied to different types of sophisticated problems in real problems.

Electricity distribution systems are considered as the most critical sectors in countries because of the essentiality of power supplement security, socioeconomic security, and way of life. According to the central role of electricity distribution systems, risk analysis helps decision maker determine the most serious risk items to allocate the optimal amount of resources and time. Probability-impact (PI) matrix is one of the most popular methods for assessment of the risks involved in the system. However, the traditional PI matrix is criticized for its inability to take into account the inherent uncertainty imposed by real-world systems. On the other hand, fuzzy sets are capable of handling the uncertainty. Thus, in this paper, fuzzy risk assessment model is developed in order to assess risk and management for electricity distribution system asset protection. Finally, a comparison analysis is conducted to show the effectiveness and the capability of the new risk assessment model.

Pipelines systems are identified to be the safest way of transporting oil and natural gas. One of the most important aspects in developing pipeline systems is determining the potential risks that implementers may encounter. Therefore, risk analysis can determine critical risk items to allocate the limited resources and time. Risk Analysis and Management for Critical Asset Protection (RAMCAP) is one of the best methodologies for assessing the security risks. However, the most challenging problem in this method is uncertainty. Therefore, fuzzy set theory is used to model the uncertainty. Thus, Fuzzy RAMCAP is introduced in order to risk analysis and management for pipeline systems. Finally, a notional example from pipeline systems is provided to demonstrate an application of the proposed methodology.