Prof. Dr.Seyed Hessameddin Zegordi | Mathematical Modeling | Best Researcher Award

Tarbiat Modares University, Iran

Professor Seyed Hessameddin Zegordi  is a distinguished academic in Industrial & Systems Engineering at Tarbiat Modares University, Tehran. With an impressive career spanning over three decades , he has made lasting contributions to academia, industry, and government. Holding a Ph.D. from Tokyo Institute of Technology , he has specialized in optimization, production systems, and supply chain disruption management. He served as department head for 9 years and contributed as a research and education deputy for 3 years . Beyond academia, Dr. Zegordi has consulted for top industrial firms and government ministries on business process reengineering and strategic systems design . Fluent in English and Japanese , he bridges global knowledge with local impact. With an h-index of 28 , he remains a thought leader in operational research and smart industrial strategies. His lifelong dedication to engineering education and innovation continues to shape the next generation of industrial experts .

Professional Profile

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Education & Experience 

Professor Zegordi earned his BSc in Industrial Engineering from Isfahan University of Technology (1987), followed by an MSc from Sharif University of Technology (1990), and later, a Ph.D. in Industrial Engineering & Management from Tokyo Institute of Technology (1994) . Starting as an Assistant Professor in 1994, he rose to become a Full Professor by 2016 . He has held key academic roles including Head of Department for 9 years and Research Deputy at the Engineering Faculty for 3 years 🏢. His industrial journey began even earlier — as General Manager at Avand Plastic and Production Planning Director at Darou Pakhsh . Since 2000, he has served as Strategy Advisor at Iran Khodro, one of the country’s largest automakers . His dual-track experience in academia and industry reflects a rare blend of theoretical depth and practical leadership, making him a mentor and innovator in industrial systems development .

Professional Development 

Prof. Zegordi has steadily advanced in both academia and industry . Starting his academic journey in 1994 as Assistant Professor, he moved up to Full Professor by 2016, based on his research, mentorship, and teaching excellence . He has led multiple strategic roles including Department Head, Research Deputy, and Education Advisor, influencing curriculum design, faculty development, and cross-disciplinary collaboration . His expertise in optimization, layout design, and supply chain disruption has made him a key consultant for national ministries and major companies like Iran Khodro . He has supervised numerous PhD and Master’s theses and is regularly invited to review scientific publications and contribute to engineering textbooks . Fluent in English and Japanese , he frequently collaborates internationally and has translated significant academic work into Farsi. Prof. Zegordi embodies a commitment to bridging theory and application in the dynamic world of industrial engineering and systems innovation .

Research Focus 

Prof. Zegordi’s research lies at the intersection of operations research, production systems, and supply chain engineering . He specializes in mathematical modeling, intelligent optimization techniques like simulated annealing and genetic algorithms, and performance measurement systems . A pioneer in disruption management, he has developed robust strategies for supply chain continuity amid uncertainties . His work in Business Process Reengineering (BPR) has been instrumental for Iran’s Ministries of Foreign Affairs, Labor, and Cooperatives, guiding institutional transformation using data-driven methods . Other focal areas include facility layout, quality function deployment (QFD), and lean manufacturing systems . By combining computational models with strategic frameworks, he enhances both tactical decision-making and long-term resilience in operations . His multidisciplinary approach, integrating engineering, management, and technology, positions him as a key contributor to the evolution of smart and sustainable industrial ecosystems .

Awards & Honors 

While specific awards were not listed, Prof. Zegordi’s accolades are reflected in his long-standing leadership, international collaborations, and scholarly achievements . With an h-index of 28 on Google Scholar , he has significantly influenced the fields of industrial engineering, optimization, and supply chain management. His publications, translated books, and invited book chapters with Springer and IGI Global demonstrate global recognition . Serving as an academic advisor and curriculum developer for nearly 30 years, he has guided numerous students to successful academic and industry careers . His selection as a consultant for national ministries and major companies like Iran Khodro signifies his trustworthiness and strategic vision at a national level . Furthermore, his multilingual abilities and cross-cultural education in Japan enhance his role in international partnerships . These cumulative honors underscore Prof. Zegordi’s reputation as a respected, forward-thinking, and impactful researcher and educator in the global engineering community .

Publication of Top Notes

1.Proposing a Model Based on Deep Reinforcement Learning for Real‑Time Scheduling of Collaborative Customization Remanufacturing

• Authors: Seyed Ali Yazdanparast; Seyed Hessameddin Zegordi; Toktam Khatibi
• Year: 2025 (published February 18, early issue dated August 2025)
• Journal: Robotics and Computer‑Integrated Manufacturing, Vol. 94, Article 102980 sciencedirect.com+9booksci.cn+9dblp.org+9
• DOI: 10.1016/j.rcim.2025.102980
• Summary: The study presents a multi-agent deep Q-network approach to schedule real-time tasks in remanufacturing customized products. Simulations in a smartphone assembly context (46,656 configurations) show the approach outperforms combined genetic algorithms, reducing factory cost by over 6%. This model addresses the challenge of disruption and real-time rescheduling in remanufacturing lines efficiently dblp.org+8booksci.cn+8ivysci.com+8.

2.The Type of Supplier Involvement in New Product Development in the Automotive Industry: Metaheuristic-based K-Means Clustering and Analytic Hierarchical Process Methods

• Authors: Esmat Taghipour Anari; Seyed Hessameddin Zegordi; Amir Albadvi
• Year: 2025 (published online January 14)
• Journal: Journal of Advances in Management Research
• DOI: 10.1108/JAMR‑03‑2024‑0095
• Summary: This article investigates supplier roles in automotive product development. Combining metaheuristic clustering and AHP methods, it categorizes supplier involvement types and their strategic importance. Contributions include a novel classification framework guiding supplier integration and collaboration in innovation contexts.

3.An Integrated System Dynamics Model of Electricity Production, Consumption, and Export Policy in Iran Considering Carbon Emissions

• Authors: Maryam Doroodi; Bakhtiar Ostadi; Ali Husseinzadeh Kashan; Seyed Hessameddin Zegordi
• Year: 2024 (October)
• Journal: Utilities Policy
• DOI: 10.1016/j.jup.2024.101795
• Summary: Using system dynamics, the study models Iran’s electricity sector, forecasting production, consumption, and export policies under carbon constraints. The model quantifies trade-offs between energy policy and emissions targets, offering strategic insights for policy adaptation.

4.A Sustainable Supply Chain Model for Time‑Varying Deteriorating Items Under Promotional Cost-Sharing Policy and Three‑Level Trade Credit Financing

• Authors: Leyla Aliabadi; Seyed Hessameddin Zegordi; Ali Husseinzadeh Kashan; Mohammad Ali Rastegar
• Year: 2024 (June)
• Journal: Operational Research
• DOI: 10.1007/s12351‑024‑00824‑x
• Summary: This research develops a sustainable supply chain framework for perishable goods, incorporating promotional cost-sharing and multi-tier trade credit. The model optimizes inventory planning, financing, and pricing under varying deterioration rates, improving profit and sustainability.

5.A Tailored Meta-Heuristic for the Autonomous Electric Vehicle Routing Problem Considering the Mixed Fleet

• Authors: Maryam Farahani; Seyed Hessameddin Zegordi; Ali Husseinzadeh Kashan
• Year: 2023
• Journal: IEEE Access
• DOI: 10.1109/ACCESS.2023.3237481
• Summary: The article proposes a customized metaheuristic algorithm to route autonomous electric vehicles in mixed fleets. The algorithm balances cost, distance, emissions, and charging constraints, offering improved routing efficiency and environmental impact.

6.A Multi‑Stage Stochastic Programming Approach for Supply Chain Risk Mitigation via Product Substitution

• Authors: Seyed Mahdi Ghorashi Khalilabadi; Seyed Hessameddin Zegordi; Ehsan Nikbakhsh
• Year: 2020 (November)
• Journal: Computers & Industrial Engineering
• DOI: 10.1016/j.cie.2020.106786
• Summary: This study formulates a stochastic programming model that enables product substitution to buffer against supply chain disruptions. The multi-stage approach balances cost, service level, and risk, offering a quantitative tool for resilient operations planning.

Conclusion

 Prof. Zegordi’s contributions bridge research innovation and strategic industrial impact. His publications in IEEE Access, Robotics and Computer-Integrated Manufacturing, and Computers & Industrial Engineering emphasize both technical rigor and societal relevance. His leadership, academic service, and collaborative industry roles make him a strong and deserving candidate for the Best Researcher Award in engineering and systems sciences.