Mehri Bagherian | Robust Optimization | Women Researcher Award

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Women Researcher Award

Mehri Bagherian
University of Guilan
Mehri Bagherian
Affiliation University of Guilan
Country Iran
Scopus ID 36105020600
Documents 18
Citations 84
h-index 5
Subject Area Robust Optimization
Event International Research Scientist Awards
ORCID 0000-0002-6870-8502

Mehri Bagherian is associated with the University of Guilan and has contributed to the field of robust optimization and decision sciences through scholarly publications and applied analytical research. Her academic profile demonstrates interdisciplinary engagement in optimization modeling, operational research, and mathematical decision-making methods. The recognition under the International Research Scientist Awards highlights her ongoing contributions to academic research and scientific development.[1]

Abstract

This article presents an overview of the academic profile and research activities of Mehri Bagherian in the area of robust optimization and operations research. Her scholarly work focuses on analytical optimization models, uncertainty management, and strategic decision-making methodologies relevant to engineering and management sciences. The article also evaluates her research influence, publication record, and suitability for recognition through the Women Researcher Award under the International Research Scientist Awards program. Her academic contributions reflect continued engagement in quantitative research and interdisciplinary scientific development.[1][2]

Keywords

Robust Optimization, Operations Research, Decision Sciences, Mathematical Modeling, Optimization Theory, Scientific Research, Women Researcher Award, Quantitative Analysis, Engineering Management, Research Recognition.

Introduction

Robust optimization has become an important research domain for addressing uncertainty and improving decision-making reliability in complex systems. Researchers working in this field contribute to optimization methodologies that support industrial planning,[1] Academic recognition programs such as the Women Researcher Award acknowledge researchers whose work contributes to scientific advancement and interdisciplinary innovation. [4]

Research Profile

Mehri Bagherian is affiliated with the University of Guilan in Iran and is academically associated with optimization-focused research areas. Her Scopus author profile indicates scholarly contributions in robust optimization and related quantitative methodologies. Her publication record demonstrates engagement in applied mathematical and operational research topics relevant to modern industrial systems.[1]

Research Contributions

The research contributions of Mehri Bagherian primarily involve optimization techniques designed to improve system reliability and strategic planning under uncertainty. Her work aligns with modern developments in operational analysis and robust decision frameworks used in engineering and management sciences.[2]

  • Development of optimization-based analytical models for uncertain environments.
  • Research on operational efficiency and mathematical decision-support systems.
  • Application of quantitative methods in engineering and industrial planning.
  • Contribution to interdisciplinary optimization and management studies.

Publications

The publication topics associated with Mehri Bagherian primarily focus on robust optimization, operational research, mathematical modeling, and decision-making under uncertainty. Her studies examine optimization strategies for improving efficiency, reliability, and analytical performance in industrial and engineering systems. The research contributes to quantitative problem-solving methodologies applicable to management sciences, logistics, and strategic operational planning.[1]

Research Impact

The research impact of Mehri Bagherian can be observed through indexed citations and continued publication activity in optimization-related domains. Citation-based indicators provide evidence of scholarly visibility and demonstrate that her work contributes to ongoing academic discussions within operational research and quantitative decision-making fields.[3] Such research areas remain relevant across engineering, industrial management, and applied mathematical sciences.[2]

Award Suitability

The Women Researcher Award recognizes individuals demonstrating sustained academic engagement, research productivity, and scholarly contribution within their respective disciplines. Mehri Bagherian’s documented publication activity, citation metrics, and specialization in robust optimization align with the evaluation criteria commonly associated with international academic recognition programs.[4]

Conclusion

Mehri Bagherian has established an academic profile centered on robust optimization and quantitative analytical research. Her indexed publications, citation record, and research engagement indicate meaningful participation in operational research and decision sciences. The Women Researcher Award article highlights her scholarly contributions and reflects the broader significance of interdisciplinary optimization research in contemporary academic environments.[1][4]

References

    1. Elsevier. (n.d.). Scopus author details: Mehri Bagherian, Author ID 36105020600. Scopus.
      https://www.scopus.com/authid/detail.uri?authorId=36105020600
    2. Bagherian, M. (2018). Unmanned aerial vehicle terrain following/terrain avoidance/threat avoidance trajectory planning using fuzzy logic. 
      https://www.researchgate.net/publication/323978826_Unmanned_Aerial_Vehicle_Terrain_FollowingTerrain_AvoidanceThreat_Avoidance_trajectory_planning_using_fuzzy_logic
    3. ORCID. (n.d.). Mehri Bagherian ORCID profile.
      https://orcid.org/0000-0002-6870-8502
    4. Zardashti, R., & Bagherian, M. (2009). A new model for optimal TF/TA flight path design problem.
      https://www.semanticscholar.org/paper/A-new-model-for-optimal-TF-TA-flight-path-design-Zardashti-Bagherian/40ac87c7d8726c7ef219048b6ae67c3a5385c535

Seyed Hessameddin Zegordi | Mathematical Modeling | Best Researcher Award

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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

SCOPUS

ORCID

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.