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Abstract: The problem of Tunnel Boring Machine (TBM) selection has a significant impact on the speed and cost of excavating sector; so that it is a strategic issue. On the other hand, selecting the optimum TBM among a pool of alternatives is a multicriteria decision making (MCDM) problem. In this paper, an evaluation model based on the fuzzy analytic hierarchy process (AHP) and another fuzzy MCDM technique, namely fuzzy technique for order performance by similarity to ideal solution (TOPSIS) is developed to help the tunneling designers in the process of the TBM selection under fuzzy environment where the vagueness and uncertainty are taken into account with linguistic variables parameterized by triangular fuzzy numbers. The fuzzy AHP is applied to form the structure of the TBM selection problem and to determine weights of the evaluation criteria, and fuzzy TOPSIS method is utilized to acquire final ranking. A real world case study is illustrated in order to demonstrate the potential of the proposed model for the TBM selection issue. It demonstrates the effectiveness and capability of the proposed model. [Copyright &y& Elsevier]

Selection of the working strategy is a critical problem and it plays a significant role in the success of organization development. On the other hand, selecting the most appropriate working strategy among a pool of alternatives is a multi-criteria decision making (MCDM) problem. Since every working strategy has its benefits and costs and may bring a company different opportunities and risks, which kind of working strategy is the most appropriate for a company to accomplish is a sophisticated and complex decision with a high degree of uncertainty. Therefore, the current paper proposed an integrated evaluation model based on the analytic network process (ANP) and the complex proportional assessment (COPRAS), to help the decision makers or managers with the selection of proper working strategy in a fuzzy environment where the fuzziness and uncertainties are handled with linguistic terms parameterized by triangular fuzzy numbers (TFNs). In this paper fuzzy ANP (FANP) is utilized to take into account interdependence and dependencies and determine the importance weights of benefit, opportunities, cost and risk (BOCR) factors, and fuzzy COPRAS is applied to rank the alternatives. To show the potential application of the proposed model, a real world application is conducted to illustrate the use of the proposed model for the working strategy selection problem. The results show the capability and effectiveness of the proposed model. [ABSTRACT FROM AUTHOR]

In the post-recession period, the business environment in developing countries is still relatively undesirable. Based on the reports published, the number of closed entrepreneurs are significantly more than the number of those newly established. These statistics also reflect that the development of entrepreneurship faces several challenges. However, a strategic management program must be accurately conducted to effectively control entrepreneurial challenges based on the limitation of time and financial resources. On the other hand, the program should provide an appropriate opportunity for competitiveness by producing better quality goods and services successfully marketed to consumers. The aim of this paper is to propose a robust model with a high potential for evaluation of entrepreneurial challenges in order to identify and control the most critical ones. To achieve the aim, the most critical parameters should be identified to prevent wasting the resources. Likewise, the analytical network process (ANP) method, a branch of multi-criteria decision making (MCDM) techniques, is a powerful tool that can consider all interrelationships and interdependencies between criteria. On the other hand, neutrosophic sets are among the most widespread approaches in coping with vagueness and unknown environment. The methodology employed in this paper uses a combination model based on ANP and neutrosophic sets using sustainable development indicators to prioritize the challenges of entrepreneurship. The results show that the proposed model has a high potential to provide a process for decision-making under a vague environment. [ABSTRACT FROM AUTHOR]