Prof. Hossein Gitinavard | Supply Chain | Best Researcher Award

Assistant Professor at Shahid Beheshti University, Iran.

Hossein Gitinavard is an accomplished researcher and academic specializing in agent-based modeling, systems analysis, and sustainable development. His work primarily focuses on optimization methods, fuzzy systems analysis, and soft computing approaches applied to sustainable supply chain management and renewable energy challenges. With a strong background in industrial engineering, he has contributed significantly to the field through innovative methodologies that enhance decision-making processes, minimize uncertainties, and improve operational efficiency. In addition to his academic contributions, he has a decade of professional experience in quality management and business process modeling, where he has worked as a management consultant to optimize organizational processes and resources, increasing productivity and reducing operational risks.

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Education Background

Hossein Gitinavard earned his Ph.D. in Industrial Engineering from Amirkabir University of Technology (Tehran Polytechnic) between 2017 and 2022. His dissertation focused on designing a biofuel supply chain network using agent-based simulation and optimization modeling. He completed his Master of Science (MSc) in Industrial Engineering at the Iran University of Science and Technology (2014–2016), where he developed a dynamic integrated hub location and routing model for perishable multi-product distribution systems under uncertainty. His academic journey began with a Bachelor of Science (BSc) in Industrial Engineering from the University of Tehran (2009–2013), where he graduated as the highest-ranking student.

Professional Development

With ten years of industry experience, Hossein has played a pivotal role in quality management and business process modeling. As a management consultant, he has worked to enhance productivity and operational efficiency across various industries by optimizing decision-making frameworks, reducing uncertainty, and minimizing losses. His expertise spans organizational process improvement, strategic resource allocation, and the implementation of advanced industrial engineering methodologies to drive business success.

Research Focus

His research interests lie in the domains of agent-based modeling, systems analysis, and sustainable development, with a particular emphasis on industrial applications. His work incorporates optimization techniques, fuzzy systems analysis, and soft computing methods to tackle complex challenges in sustainable supply chain management and renewable energy systems. By integrating mathematical modeling with computational intelligence, he aims to develop innovative solutions for environmental and industrial sustainability.

Author Metrics:

Hossein Gitinavard has an impressive research impact, with 1,240 citations, an h-index of 24, and an i10-index of 34. His scholarly contributions are widely recognized in the academic community, and he has published numerous influential papers in high-impact journals. His research has been instrumental in advancing methodologies for industrial decision-making, renewable energy solutions, and supply chain optimization.

Honors & Awards

He has received multiple accolades for his contributions to research and academia. He serves as an Editorial Board Member for the International Innovator Awards, recognizing his significant achievements in innovative research. He is a member of the Young Researchers and Elite Club and has been honored as the top researcher at the Iran University of Science and Technology. His academic excellence has been acknowledged with the FOE award from the University of Tehran and the highest-ranking student awards for both his MSc and BSc degrees. Additionally, he has received the Best Paper Award at the International Conference on Industrial Engineering and Management in Malaysia (IEEE, 2014).

Editorial and Reviewer Roles

As a highly regarded researcher, Hossein is an honorary reviewer for top-tier journals, including Nature Sustainability, Information Sciences, International Journal of IEEE Access, European Journal of Operational Research, and International Journal of Production Research. His expertise in evaluating and reviewing high-quality research has contributed to advancing knowledge in industrial engineering and sustainable systems.

Publication Top Notes

1. A soft computing-based modified ELECTRE model for renewable energy policy selection with unknown information

• Authors: M. Mousavi, H. Gitinavard, S. M. Mousavi
• Journal: Renewable and Sustainable Energy Reviews
• Volume: 68
• Pages: 774-787
• Year: 2017
• Citations: 119
• Summary: This paper proposes a modified ELECTRE model based on soft computing techniques to address renewable energy policy selection when dealing with incomplete or uncertain information. The model improves decision-making reliability by integrating advanced multi-criteria decision analysis (MCDA) methods.

2. A new multi-criteria weighting and ranking model for group decision-making analysis based on interval-valued hesitant fuzzy sets to selection problems

• Authors: H. Gitinavard, S. M. Mousavi, B. Vahdani
• Journal: Neural Computing and Applications
• Volume: 27
• Pages: 1593-1605
• Year: 2016
• Citations: 87
• Summary: This paper presents a novel weighting and ranking model for group decision-making using interval-valued hesitant fuzzy sets. The approach enhances selection processes in uncertain environments, particularly for applications requiring subjective expert opinions.

3. Green supplier evaluation in manufacturing systems: a novel interval-valued hesitant fuzzy group outranking approach

• Authors: H. Gitinavard, H. Ghaderi, M. S. Pishvaee
• Journal: Soft Computing
• Volume: 22
• Pages: 6441-6460
• Year: 2018
• Citations: 81
• Summary: This study develops an interval-valued hesitant fuzzy outranking approach for green supplier evaluation in manufacturing systems. The methodology improves sustainability assessments by integrating advanced fuzzy decision-making techniques.

4. Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

• Authors: M. P. Borujeni, H. Gitinavard
• Journal: Journal of Sustainable Mining
• Volume: 16 (4)
• Pages: 207-218
• Year: 2017
• Citations: 70
• Summary: This paper introduces an imprecise last aggregation preference selection index (LAPSI) method for sustainable mining contractor selection. The approach accounts for uncertainty in decision-making, improving contractor evaluation in the mining sector.

5. Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems

• Authors: H. Gitinavard, S. M. Mousavi, B. Vahdani
• Journal: Soft Computing
• Volume: 21
• Pages: 3247-3265
• Year: 2017
• Citations: 67
• Summary: This research proposes a new interval-valued hesitant fuzzy group assessment method that incorporates last aggregation techniques for multi-criteria decision-making in industrial applications.

6. A Bi-Objective Multi-Echelon Supply Chain Model with Pareto Optimal Points Evaluation for Perishable Products Under Uncertainty

• Authors: H. Gitinavard, S. H. Ghodsypour, M. Akbarpour Shirazi
• Journal: Scientia Iranica
• Volume: 26 (5)
• Pages: 2952-2970
• Year: 2019
• Citations: 24
• Summary: This paper presents a bi-objective multi-echelon supply chain model specifically designed for perishable products under uncertain conditions.

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