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Seyed Meysam Mousavi

Researcher at Shahed University

Publications -  74
Citations -  1223

Seyed Meysam Mousavi is an academic researcher from Shahed University. The author has contributed to research in topics: Fuzzy logic & Fuzzy set. The author has an hindex of 15, co-authored 74 publications receiving 802 citations. Previous affiliations of Seyed Meysam Mousavi include Islamic Azad University & University of Tehran.

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Integrated product-process design: Material and manufacturing process selection for additive manufacturing using multi-criteria decision making

TL;DR: A generic decision methodology is introduced that will not only provide a set of compromised AM materials, processes and machines but will also act as a guideline for designers to achieve a strong foothold in the AM industry by providing practical solutions containing design oriented and feasible material-machine combinations from a current database of 38 renowned AM vendors.
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A soft computing based-modified ELECTRE model for renewable energy policy selection with unknown information

TL;DR: A new decision model based on modified elimination and choice translating reality (ELECTRE) is presented under a hesitant fuzzy environment for solving the multi-attribute group decision-making (MAGDM) problems in energy sector.
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R&D project evaluation and project portfolio selection by a new interval type-2 fuzzy optimization approach

TL;DR: A new model that applies IT2FSs to handle uncertainty, uses semi-variance to assess risk, synchronously considers risk and return in its selection process, and addresses the considerations and limits of real-world problems is proposed.
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A New Group Decision Model Based on Grey-Intuitionistic Fuzzy-ELECTRE and VIKOR for Contractor Assessment Problem

TL;DR: In this paper, a new decision model with multi-criteria analysis by a group of decision makers (DMs) with intuitionistic fuzzy sets (IFSs) was introduced, which depends on a new integration of IFSs theory, ELECTRE and VIKOR along with grey relational analysis.
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Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems

TL;DR: This paper proposes a novel soft computing approach, namely IVHF-MCGA, based on new interval-valued hesitant fuzzy complex proportional assessment method that can be applied in solving the multi-criteria group decision-making (MCGDM) problems under uncertainty.