S
S. Meysam Mousavi
Researcher at Islamic Azad University
Publications - 11
Citations - 570
S. Meysam Mousavi is an academic researcher from Islamic Azad University. The author has contributed to research in topics: Fuzzy logic & Fuzzy set. The author has an hindex of 11, co-authored 11 publications receiving 522 citations. Previous affiliations of S. Meysam Mousavi include Islamic Azad University South Tehran Branch & Iran University of Science and Technology.
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Project risk identification and assessment simultaneously using multi-attribute group decision making technique
TL;DR: In this article, a new methodology for identifying and assessing risks simultaneously by applying MAGDM technique is presented, which includes a new procedure for classifying potential risks which it is named potential risk breakdown structure (PRBS) based on project work breakdown structure.
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A fuzzy integrated methodology for evaluating conceptual bridge design
TL;DR: The results demonstrated that the proposed methodology could be successfully applied in the highway bridge projects as a useful tool to facilitate decision making.
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A new compromise solution method for fuzzy group decision-making problems with an application to the contractor selection
TL;DR: A novel compromise solution method for solving fuzzy group decision-making problems by a group of experts, which can determine the best alternative by considering both conflicting quantitative and qualitative evaluation criteria in real-life applications is presented.
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Soft computing-based preference selection index method for human resource management
TL;DR: An Interval-Valued Fuzzy Preference Selection Index IVF-PSI method aiming at solving complex decision making problems, in which the performance ratings of candidates are described by using the concept of the IVFSs.
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Soft computing based on a fuzzy grey group compromise solution approach with an application to the selection problem of material handling equipment
TL;DR: The proposed fuzzy grey group compromise ranking method helps the decision-makers to evaluate the gaps that have not been reduced or improved for the alternatives under uncertainty in order to have the great benefit.