Jafar Fathali | Operations Research | Best Researcher Award

Prof.Jafar Fathali | Operations Research | Best Researcher Award

University Professor at Shahrood University of Technology, Iranย 

Professor Jafar Fathali ๐ŸŽ“ is a renowned academic in Operations Research and Applied Mathematics, currently serving as a Professor at the Faculty of Mathematical Sciences, Shahrood University of Technology, Iran ๐Ÿ‡ฎ๐Ÿ‡ท. With decades of contribution to location theory, heuristic optimization, and scheduling problems , he has become a distinguished figure in computational mathematics. A prolific researcher, Prof. Fathali has authored over 50+ peer-reviewed journal articlesย  in internationally recognized platforms such as EJOR, Soft Computing, and Computers & Industrial Engineering. He is actively involved in scholarly communities including the Iranian Mathematical Society and the Iranian Operations Research Society . Beyond research, he contributes as a referee for leading journals, mentoring students and advancing mathematical modeling in real-world applications. His academic journey is defined by innovation, persistence, and leadership , making him a vital contributor to the global research ecosystem .

๐Ÿ”นProfessional Profile

SCOPUS

ORCID

๐Ÿ“˜ Education & Experience

Prof. Jafar Fathali holds a BSc in Applied Mathematics from Ferdowsi University of Mashhad , an MSc from Amirkabir University of Technology , and earned his Ph.D. in Applied Mathematics from Ferdowsi University in 2005 . With a solid foundation in mathematical theories, he began teaching at Shahrood University of Technology, where he advanced to a full professorship . Over the years, he has taught a wide array of undergraduate and graduate courses, including Operations Research, Advanced Linear & Nonlinear Programming, Combinatorial Optimization, and Numerical Analysis . His expertise spans both theoretical frameworks and practical applications, equipping students with problem-solving and analytical skills ๐Ÿ”. With his academic and mentoring experience, Prof. Fathali has played a key role in shaping Iranโ€™s next generation of mathematicians and operations research .

๐Ÿš€ Professional Development

Professor Fathali has shown remarkable growth in academia through innovative research, interdisciplinary collaborations, and active journal reviewing . He has reviewed articles for top-tier journals such as European Journal of Operational Research, Transportation Research Part E, Soft Computing, and Optimization Methods and Software . He is a member of the Iranian Mathematical Society, Iranian Operations Research Society, and Iranian Statistics Society , reflecting his deep involvement in the academic community. His ability to integrate fuzzy logic, graph theory, and metaheuristic algorithms into practical models has enhanced decision-making strategies across industries . Prof. Fathali has also co-developed numerous hybrid algorithms involving genetic algorithms, ant colony optimization, and variable neighborhood search for solving complex problems . His active mentorship, editorial contributions, and research collaborations are key indicators of a career deeply committed to academic excellence, growth, and innovation .

๐Ÿ”ฌ Research Focus

Professor Jafar Fathaliโ€™s research is firmly rooted in Operations Research, with an emphasis on location theory , combinatorial optimization, and scheduling problems . He specializes in designing algorithms for complex decision-making models such as the p-median, p-center, and core location problems across graphs and trees . His methods employ heuristic techniques, metaheuristics (e.g., genetic algorithms , particle swarm optimization , and fuzzy logicย  to model real-world uncertainties in logistics, network design, and resource allocation. Prof. Fathali has also explored inverse and semi-obnoxious location problems, expanding the scope of location models to account for service inefficiencies and backup facilities . His works address both theoretical and applied aspects, blending mathematical rigor with practical implementation . With continuous innovations in modeling and optimization, his contributions have significantly advanced the field of applied mathematics and operations research .

๐Ÿ† Awards & Honors

While specific awards and honors for Professor Jafar Fathali are not individually listed, his academic reputation is underscored by the impact and volume of his scholarly work . Having published in high-impact journals like European Journal of Operational Research and Soft Computing, his research has earned wide recognition and citation ๐Ÿ†. Being a referee for over a dozen international journals and collaborating with well-known scholars such as R.E. Burkard, indicates peer acknowledgment and respect .ย His sustained publication record, editorial engagements, and frequent invitations to review complex mathematical models highlight his research excellence and international credibility . His contributions have helped define solutions for complex logistics and scheduling challenges, securing his place among Iran’s most influential operations researchย . With ongoing recognition from both academic institutions and scholarly circles, Prof. Fathali continues to be a role model for aspiring mathematicians and OR specialists globally .

๐Ÿ”นPublication of Top Notes

1.Convexity and sensitivity analysis of the median line location problem

Authors: Mehdi Golpayegani, Jafar Fathali
Year: 2025
Journal: International Journal of Systems Science: Operations & Logistics
DOI: 10.1080/23302674.2025.2529967

2.Greedy algorithms for the inverse center line location problem

Authors: Mehdi Golpayegani, Jafar Fathali
Year: 2025
Journal: Expert Systems with Applications
DOI: 10.1016/j.eswa.2025.129064

3.Fuzzy balanced allocation problem with efficiency on facilities

Authors: Azam Azodi, Jafar Fathali, Mojtaba Ghiyasi, Tahereh Sayar
Year: 2023
Journal: Soft Computing
DOI: 10.1007/s00500-022-07695-4

4.The balanced 2-median and 2-maxian problems on a tree

Authors: Jafar Fathali, Mehdi Zaferanieh
Year: 2023
Journal: Journal of Combinatorial Optimization
DOI: 10.1007/s10878-023-00997-9

5.Finding the absolute and vertex center of a fuzzy tree

Authors: Fatemeh Taleshian, Jafar Fathali, Nemat Allah Taghi-Nezhad
Year: 2022
Journal: Transportation Letters
DOI: 10.1080/19427867.2021.1909797

6.The minimum information approach to the uncapacitated p-median facility location problem

Authors: Mehdi Zaferanieh, Maryam Abareshi, Jafar Fathali
Year: 2022
Journal: Transportation Letters
DOI: 10.1080/19427867.2020.1864595

7.Fuzzy Balanced Allocation Problem with Efficiency on Servers

Authors: Azam Azodi, Jafar Fathali, Mojtaba Ghiyasi, Tahereh Sayar
Year: 2021
Type: Preprint
DOI: 10.21203/rs.3.rs-444116/v1

8.Inverse and reverse balanced facility location problems with variable edge lengths on trees

Authors: Shahede Omidi, Jafar Fathali, Morteza Nazari
Year: 2020
Journal: OPSEARCH
DOI: 10.1007/s12597-019-00428-6

9.Finding an optimal core on a tree network with M/G/c/c state-dependent queues

Authors: Mehrdad Moshtagh, Jafar Fathali, James MacGregor Smith, Nezam Mahdavi-Amiri
Year: 2019
Journal: Mathematical Methods of Operations Research
DOI: 10.1007/s00186-018-0651-3

10.The Stochastic Queue Core problem, evacuation networks, and state-dependent queues

Authors: Mehrdad Moshtagh, Jafar Fathali, J. MacGregor Smith
Year: 2018
ย Journal: European Journal of Operational Research
ย DOI: 10.1016/j.ejor.2018.02.026

๐ŸConclusion

Professor Fathaliโ€™s research stands out due to its mathematical rigor, practical relevance, and algorithmic innovation. His work significantly advances the optimization and decision sciences field, contributing both theoretical frameworks and practical solutions. These qualities, combined with his sustained academic output, collaborative spirit, and international impact, make him an ideal candidate for the Best Researcher Award.

Ramin Ahadi | Operations Research | Best Researcher Award

Mr.Ramin Ahadi | Operations Research | Best Researcher Award

Mr.Ramin Ahadi , University of Cologne , Germany

A final-year Ph.D. candidate ๐ŸŽ“ at the University of Cologne and IE Business School, this researcher specializes in practical operations management and data science. Their work focuses on developing intelligent decision support systems using agent-based simulation ๐Ÿง , machine learning ๐Ÿค–, and deep reinforcement learning. With expertise in smart mobility ๐Ÿš—โšก, energy systems โšก๐ŸŒ, and sustainability, they bridge real-world problems with cutting-edge technology. Fluent in Python and other tools, they actively teach ML to graduate students ๐Ÿ“˜ and collaborate across academia and industry. Passionate about climate solutions ๐ŸŒฑ, they aim to innovate for a greener and smarter world. ๐ŸŒ๐Ÿ’ก

Professional Profile

Google Scholar

Education & Experienceย 

Holding a Ph.D. (2025 exp.) in Information Systems & Operations Management from the University of Cologne ๐ŸŽ“ and currently a visiting scholar at IE Business School, Madrid ๐Ÿ‡ฉ๐Ÿ‡ช๐Ÿ‡ช๐Ÿ‡ธ, they also earned M.Sc. and B.Sc. degrees in Iran ๐Ÿ‡ฎ๐Ÿ‡ท in Industrial and Mechanical Engineering respectively. With roles as researcher, lecturer ๐Ÿ‘จโ€๐Ÿซ, and tutor, their journey spans Europe and Asia. Theyโ€™ve worked on EU-level energy and mobility research projects, simulations for EV fleets โšก๐Ÿš—, and optimization algorithms. Teaching advanced analytics, leading grants, and collaborating with cities like Berlin and Paris ๐ŸŒ, they blend deep technical skills with real-world impact.

Professional Developmentย 

This candidate continuously enhances their skill set through hands-on research, collaborative grant writing ๐Ÿ’ผ, and academic publishing ๐Ÿ“š. They lead cutting-edge projects using Python, TensorFlow, PyTorch, and simulation tools like Simpy and Pyomo ๐Ÿ–ฅ๏ธ. Their development includes teaching graduate-level machine learning courses ๐Ÿ‘จโ€๐Ÿซ, engaging in high-impact conferences like ICIS and AAMAS ๐Ÿ›๏ธ, and working with institutions like EWI. Industry collaborations include EV charging systems and sustainable logistics ๐Ÿš›๐Ÿ”‹. Their commitment to sustainability, innovation, and smart city solutions ๐ŸŒ‡ positions them as a future leader in technology-driven operations management.

Research Focusย 

Their research centers on smart mobility ๐Ÿš—โšก, energy systems ๐Ÿ”‹๐ŸŒ, and climate-conscious technologies ๐ŸŒฑ. They design agent-based simulations and deep learning models ๐Ÿง  to manage shared autonomous fleets and EV charging. Key areas include dynamic fleet pricing, ride-hailing, digital twins of mobility networks ๐ŸŒ, and predictive analytics for load scheduling. They bridge theory and application by leveraging real-world data from European cities ๐Ÿ™๏ธ. Using advanced optimization (GA, MPC, RL) and simulation, their work contributes to more sustainable urban ecosystems. Their core mission is to build data-driven, adaptive platforms for smarter, greener cities. ๐ŸŒ†๐Ÿ“ˆ

Awards & Honorsย 

Recognized for academic excellence and innovation ๐Ÿ†, they ranked in the top 5% during their M.Sc. and top 10% in their B.Sc. programs ๐ŸŽ“. They earned a competitive research scholarship from the Institute of Energy Economics at the University of Cologne ๐Ÿ’ก and co-led multiple successful EU research grant proposals ๐ŸŒ. Their work has been presented at top-tier conferences like ICIS, ECIS, and WITS ๐Ÿ›๏ธ. Theyโ€™ve also made an impact through teaching awards and invitations to speak on sustainability in mobility and energy systems ๐Ÿš€. Their excellence extends to both academia and industry collaborations. ๐Ÿ‘จโ€๐Ÿ”ฌ๐Ÿ“Š

Publication Top Notes

1.Ahadi, R., Ketter, W., Collins, J., & Daina, N. (2023).
“Cooperative Learning for Smart Charging of Shared Autonomous Vehicle Fleets.”
Transportation Science, 57(3), 613โ€“630.
๐Ÿ” Summary: This study presents a cooperative learning framework for optimizing electric vehicle (EV) charging across shared autonomous vehicle fleets. The model integrates real-time learning with coordination strategies to improve efficiency, grid stability, and user satisfaction.

2.Khalilzadeh, M., Neghabi, H., & Ahadi, R. (2023).
“An Application of Approximate Dynamic Programming in Multi-Period Multi-Product Advertising Budgeting.”
Journal of Industrial & Management Optimization, 19(1).
๐Ÿ” Summary: This paper develops an approximate dynamic programming approach to optimize advertising budgets over time for multiple products. It accounts for intertemporal trade-offs and uncertain returns, showcasing the method’s superiority to static approaches.

3.Yazdi, L., Ahadi, R., & Rezaee, B. (2019).
“Optimal Electric Vehicle Charging Station Placing with Integration of Renewable Energy.”
15th Iran International Industrial Engineering Conference (IIIEC), 47โ€“51.
๐Ÿ” Summary: This conference paper investigates optimal site selection for EV charging stations using a multi-objective model that includes renewable energy generation and urban demand forecasting.

Conclusion

R. Ahadi exemplifies the qualities of a future-leading scholar with impactful, sustainable, and innovative contributions to operations management and intelligent systems. Their work directly contributes to the global challenge of building greener, smarter urban ecosystemsโ€”making them highly deserving of the Best Researcher Award. ๐ŸŒ๐Ÿ†

 

Dr. Vahideh Bafandegan Emroozi | Maintenance | Women Researcher Award

Dr. Vahideh Bafandegan Emroozi | Maintenance | Women Researcher Award

Author , Ferdowsi university of Mashhad , Iran

Vahideh Bafandegan Emroozi is a passionate Iranian researcher specializing in industrial management and optimization. ๐ŸŽ“ With a Ph.D. from Ferdowsi University of Mashhad, her work bridges technology and human-centric approaches. ๐Ÿ“Š Her research spans supply chain innovation, IoT applications, and human error analysis. ๐Ÿค–๐Ÿง  She has published in esteemed journals and held research fellowships at Ferdowsi and Sanabad Universities. ๐Ÿ“šโœ๏ธ Known for her analytical skills and academic dedication, Vahideh continues to contribute significantly to industrial systems and decision sciences. ๐Ÿ”๐Ÿ“ˆ Her collaborative spirit and teaching experience further highlight her dynamic role in academia. ๐Ÿ‘ฉโ€๐Ÿซ๐ŸŒ

Professional Profile:

SCOPUS

Education & Experience:

Vahideh earned her Ph.D. in Industrial Management (2019โ€“2024) ๐ŸŽ“ from Ferdowsi University, where her thesis focused on IoT-based maintenance and human error modeling. ๐Ÿ“ก๐Ÿ› ๏ธ She also completed an M.Sc. in Industrial Management (2014โ€“2017) with a high GPA of 18.96/20 ๐Ÿ“š and a B.Sc. in Industrial Engineering (2008โ€“2012). ๐Ÿ—๏ธ Her academic journey led to research fellow roles at Ferdowsi University (2021โ€“2023) and Sanabad University (2023โ€“2024). ๐Ÿ”ฌ๐Ÿ›๏ธ In addition to research, she has taught Operations Research, Strategic Management, and Multi-Criteria Decision Making. ๐Ÿ‘ฉโ€๐Ÿซ Her experience reflects a strong foundation in both theory and application. ๐Ÿ’ผ๐Ÿงฎ

Professional Development:

Vahideh continually builds her academic and technical skills through professional development. ๐Ÿ“ˆ๐Ÿ’ก She has mastered analytical and modeling tools such as Python, MATLAB, GAMS, LINGO, LaTeX, and Vensim. ๐Ÿ’ป๐Ÿ“ Her commitment to research excellence is evident in her publications in Scopus-indexed journals ๐Ÿ“„๐Ÿ” and her work on complex topics like green supply chain management and pandemic response strategies. ๐ŸŒ๐Ÿ“ฆ She actively contributes to knowledge dissemination through teaching, collaborative research, and methodological innovation. ๐Ÿ“Š๐Ÿง  Her engagement with multidisciplinary topics ensures she remains at the forefront of industrial and systems engineering. ๐Ÿš€๐Ÿ“˜

Research Focus:

Vahidehโ€™s research spans across multiple domains in industrial management. ๐Ÿญ๐Ÿ” Her core interests include supply chain management, optimization, and maintenance planning. ๐Ÿงพ๐Ÿ› ๏ธ She also explores the effects of human error, reliability analysis, and inventory control systems. โš™๏ธ๐Ÿง ๐Ÿ“ฆ A significant part of her work integrates the Internet of Things (IoT) ๐ŸŒ with system dynamics and mathematical modeling ๐Ÿ“Š๐Ÿ“‰ to improve industrial decision-making. Her goal is to create smarter, more resilient, and sustainable industrial systems. ๐ŸŒฑ๐Ÿ’ก Her innovative contributions are driving progress in operational efficiency and risk reduction. ๐Ÿšš๐Ÿ“ˆ

Awards & Honors:

While specific awards were not listed, Vahidehโ€™s academic record speaks to her excellence. ๐ŸŒŸ She achieved outstanding GPAs in both her Ph.D. (19.49/20) and M.Sc. (18.96/20) programs. ๐Ÿฅ‡๐Ÿ“˜ Her research has been recognized with publications in high-impact international journals like Process Integration and Optimization for Sustainability and Journal of Industrial and Management Optimization. ๐Ÿ“šโœจ She has contributed novel methodologies in green supplier selection, VIKOR optimization, and system dynamics during COVID-19. ๐Ÿงช๐ŸŒ Her roles as research fellow at top Iranian universities also reflect her academic merit and potential. ๐Ÿ›๏ธ๐Ÿ”ฌ

Publication Top Notes

1. Markov Chain-Based Model for IoT-Driven Maintenance Planning with Human Error and Spare Part Considerations

Authors: Bafandegan Emroozi, Vahideh; Doostparast, Mahdi
Journal: Reliability Engineering and System Safety
Year: 2025
Access: Open Access
Citations: 0 (as of now)

๐Ÿ” Summary:
This article introduces a novel Markov chain-based framework that integrates the Internet of Things (IoT) into industrial maintenance planning. The model accounts for human error probabilities and spare part availability, creating a dynamic and realistic approach to predictive maintenance. ๐Ÿ“ˆ The use of Markov chains enables the system to model stochastic transitions between equipment states, improving decision-making accuracy. ๐Ÿค–๐Ÿ“ฆ The study enhances reliability and safety in industrial systems by aligning IoT data with probabilistic risk and resource planning, offering a scalable tool for real-time maintenance strategy optimization. ๐Ÿ› ๏ธ๐Ÿ“Š

2. Enhancing Industrial Maintenance Planning: Optimization of Human Error Reduction and Spare Parts Management

Authors: Bafandegan Emroozi, Vahideh; Kazemi, Mostafa; Doostparast, Mahdi
Journal: Operations Research Perspectives
Year: 2025
Access: Open Access
Citations: 0 (as of now)

๐Ÿ” Summary:
This paper proposes an optimization model aimed at improving maintenance planning by focusing on human error mitigation and efficient spare parts management. ๐Ÿ‘ทโš™๏ธ It applies advanced operations research techniques to identify cost-effective strategies for minimizing failures and delays due to incorrect human actions or resource shortages. The model bridges the gap between human factors engineering and logistical planning, integrating real-time data and decision analysis. ๐Ÿง ๐Ÿ“ฆ It offers a comprehensive framework suitable for modern industries aiming to balance cost, reliability, and safety. ๐Ÿงพ๐Ÿ“‰

Conclusion

Vahideh Bafandegan Emroozi exemplifies the qualities celebrated by Women in Research Awards: innovation, impact, leadership, and academic excellence. ๐ŸŒŸ Her work addresses critical industrial challenges through smart technologies and rigorous modeling, while her dedication to teaching and mentoring amplifies her influence. As a pioneering female researcher in a highly technical and traditionally male-dominated field, she is not only technically accomplished but also a role model for aspiring women in STEM. ๐Ÿง ๐Ÿ”ฌ๐Ÿ‘ฉโ€๐Ÿซ She is highly deserving of recognition through a Women Researcher Award.