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Nilgun Fescioglu-UnverView profile

Associate Professor

• Production Systems
• Service Systems
• Simulation
• +7 more

Assoc. Prof. Dr. Nilgün Fescioglu-Unver serves as faculty in the Department of Industrial Engineering at TOBB University of Economics and Technology in Ankara, Turkey. With expertise spanning production systems, simulation, and healthcare applications, she teaches courses ranging from foundational Industrial Engineering to advanced simulation topics and sustainable engineering. Education: PhD, Industrial Engineering, Northeastern University, Boston, MA, 2008 MS, Information Systems, Northeastern University, Boston, MA, 2002 MBA, Business Administration, Middle East Technical University, 2000 MS, Mechanical Engineering, Middle East Technical University, 1998 BS, Mechanical Engineering, Middle East Technical University, 1995 Her research focuses on practical applications of simulation in complex systems, with particular emphasis on healthcare logistics, sustainable manufacturing, and service operations. Her work bridges theoretical simulation methodologies with real-world implementation challenges across various industries. Current research directions include self-adaptive software systems for resource allocation and decision support in dynamic environments. Her recent publications demonstrate a consistent focus on simulation-based optimization for blood supply chains, airport operations, sustainable receiving systems, and manufacturing efficiency. These works highlight her expertise in applying discrete-event simulation to solve complex resource allocation problems across diverse sectors. Scientific Awards: Academic Advising Award – TUBITAK 2241- Graduation Projects for Industry, 2016 Phi Beta Delta Honor Society Membership, 2006 Who's Who in American Colleges and Universities Listing, 2004 Industrial Engineering Honor Society Alpha Pi Mu Membership, 2004 Outstanding Teaching Assistant Award, Northeastern University, 2003 Honor Student, Middle East Technical University, 1991-1995 As an academic advisor, she has supervised four Master's theses on electric vehicle charging systems, healthcare real-time locating systems, and asset tracking. Her grant portfolio includes significant projects funded by TUBITAK and TEYDEB, with principal investigator roles on electric vehicle charging station management and consultancy for energy resource management systems. These projects demonstrate strong industry-academia collaboration with organizations including ENERJISA and Arçelik. Her work connects academic research with industrial applications through projects addressing eco-efficient production systems and smart energy management, creating tangible impacts in Turkey's manufacturing and service sectors.

Andreas KleineView profile

Professor

• Operations Research
• Data Envelopment Analysis
• Multi-Criteria Decision Making
• +4 more

Univ.-Prof. Dr. Andreas Kleine is a distinguished Professor at Distance University Hagen, holding the Chair of Business Administration, specializing in Quantitative Methods and Business Mathematics within the Faculty of Economics and Business Administration. Since 2011, he has led this department while also serving in significant administrative roles including as Vice Rector for Research and the Promotion of Young Academics (2016-2022) and currently as Ombudsperson for ensuring good scientific practice since March 2022. He is an active member of the research focus Energy, Environment & Sustainability and the research group Management of Energy-Flexible Factories (MaxFab). Saarland University - Diplom-Kaufmann in Business Administration (1989) Habilitation in Business Administration (2001) with thesis "Efficient Alternatives, Productions, and Organizations" University of Hohenheim - Chair of Operations Research (2002) and Department of Quantitative Methods Aston Business School - Visiting Scholar (2005) Württemberg Academy of Administrative and Economic Sciences - Teaching Experience Professor Kleine's research centers on applying quantitative methods to business administration problems, particularly where information is incomplete or multiple objectives must be balanced simultaneously. His work spans Data Envelopment Analysis, Multi-Criteria Decision Making, Optimization of renewable energies, and Risk Measurement. He has extensive experience in energy economics, focusing on how energy consumption and emissions in economic units can be recorded and operational processes optimized through energy flexibility potential. His research also explores optimal control of PV systems, forecasting electricity generation from renewables, and sustainability in production planning. Analyzing his recent publications reveals a strong trend toward sustainable operations research with emphasis on energy-flexible production systems, eco-efficient manufacturing, and multi-criteria optimization for sustainability. His work bridges theoretical operations research with practical applications in energy markets, production planning, and environmental management, often employing advanced methods like Data Envelopment Analysis and Pareto optimization to address complex sustainability challenges. Editor in Chief: Lecture Notes in Economics and Mathematical Systems Editorial Board: Journal of Business Economics Scientific Committee: International Conference on Data Envelopment Analysis (2023, 2017, 2016, 2015) Chair of Program Committee: VHB Annual Conference 2017 (St. Gallen) Chair of Scientific Commission "Operations Research" of VHB (2011-2015) Professor Kleine has served as reviewer for numerous prestigious journals including Annals of Operations Research, European Journal of Operational Research, and Journal of Business Economics. His research has been funded by both the German Research Foundation (DFG) and industry partners like TransnetBW for projects related to renewable energy market integration. He has played a key role in establishing the Research and Graduate Services at Distance University and served on the CRIS.NRW steering committee as representative of Vice Rectors for Research in North Rhine-Westphalian universities. As a member of the interdisciplinary research project MaXFab (Management Energieflexibler Fabriken) and the research focus on Energy, Environment & Sustainability, Professor Kleine collaborates with engineers, economists, and environmental scientists to develop practical solutions for energy-flexible production systems. His work with the Ombuds office for scientific integrity demonstrates his commitment to maintaining high research standards across the university.

Emre BerkView profile

Professor

• Operations Management
• Supply Chain Management
• Inventory Control
• +4 more

Emre Berk is a Professor at Bilkent University's Faculty of Business Administration, specializing in Operations Management. He holds a PhD in Operations Management from the University of Washington and has taught at institutions such as MIT at Zaragoza and Texas A&M. His research focuses on perishable inventory control, supply chain dynamics, and sustainable operations. Berk has been funded by NSF and TÜBİTAK, with publications in top journals like Management Science and Operations Research. He currently serves as an Associate Editor for IISE Transactions. Education: B.S. in Mechanical Engineering, Bogazici University M.S. in Mechanical Engineering, Washington State University (Fulbright Scholar) MBA and PhD in Operations Management, University of Washington Research Interests: Revenue Management Supply Chain Strategy Perishable Inventory Systems Information-Driven Inventory Policies Carbon Economies Optimization of Decentralized Systems His recent work explores inventory systems under uncertainty, sustainability in operations, and disruption resilience. Over 30 peer-reviewed articles highlight his contributions to inventory theory, stochastic modeling, and supply chain economics. Grants & Funding: NSF (National Science Foundation) TÜBİTAK (Turkish Scientific Council)

Raf JansView profile

Professor

• Operations Management
• Production Planning
• Operations Research Applications
• +3 more

Raf Jans is a Professor in the Department of Logistics and Operations Management at HEC Montréal. He holds the Chair in Supply Chain Operations Planning and serves as the Academic Supervisor for the Ph.D. in Logistics and Operations Management. His research focuses on Operations Management, Production Planning, and Applications of Operations Research, with expertise in Integer Programming and Combinatorial Optimization. Education: B.Sc. and M.Sc. in Business Engineering, Katholieke Universiteit Leuven (KU Leuven); Ph.D. in Applied Economics and Operations Research, KU Leuven. Research Interests: His work addresses supply chain optimization, stochastic lot-sizing, vehicle routing, inventory management, and decomposition methods. He collaborates with CIRRELT and GERAD research centers, contributing to large-scale operational problems in logistics and production systems. Publications (2020–2025): Focus on integrated production-transportation systems, stochastic optimization, and heuristic algorithms for complex supply chain challenges. Recent topics include line balancing, lot-sizing with storage allocation, and emission-constrained routing. Advising: Supervised 4 Ph.D., 5 M.Sc., and 24 project students on topics ranging from supply chain transformation to production scheduling and inventory segmentation. Collaborates with industry partners like Bombardier and Pratt & Whitney Canada. Labs/Teams: Active member of CIRRELT (Interuniversity Research Centre on Enterprise Networks) and GERAD (Group for Research in Decision Analysis).

Thomas VoßView profile

Researcher

• Reinforcement Learning
• Manufacturing Systems
• Production Optimization
• +5 more

Thomas Voß is a Researcher at Leuphana University of Lüneburg, affiliated with the School of Business and the Department of Production Technology and Systems. His work bridges theoretical computer science with practical manufacturing applications, focusing on intelligent optimization of production systems. Dr. Voß's research interests include: Application of reinforcement learning to manufacturing challenges Dynamic scheduling and sequencing in flexible production environments Energy optimization in industrial processes Simulation-based decision support systems Intelligent control of production systems His publication record demonstrates a consistent focus on applying machine learning techniques, particularly reinforcement learning, to solve complex production optimization problems. The research trajectory shows progression from theoretical models to practical implementations in manufacturing systems, with increasing emphasis on energy efficiency and adaptive control mechanisms in recent work. Dr. Voß has received recognition for his contributions: ACM-SIGSIM Best Ph.D. Student Paper Award (2020) Award for Outstanding Presentations at Open Conferences (2017) e-fellows.net scholarship recipient (2017) Certificate of Honor from the Institute for Product and Process Innovation (2016) He actively participates in major academic conferences including the Winter Simulation Conference and the Conference on Manufacturing Systems. His current projects include research on intelligent pump control systems for energy optimization and the development of individualized production systems through the IFIPro project.

• Supply Chain Management
• Operations Research
• Revenue and Pricing Management
• +5 more

Hyun-Soo Ahn is a Professor of Technology and Operations and Ford Motor Co. Director of the Tauber Institute for Global Operations at the University of Michigan's Stephen M. Ross School of Business. His research focuses on supply chain management, service operations, pricing strategies, and value chain innovations, supported by NSF and Department of Energy grants. He teaches business analytics, machine learning, and consulting methodologies across EMBA, MBA, MSCM, and BBA programs, along with executive education for firms like ICBC and Bank of America. Education: PhD in Technology and Operations, University of Michigan (2001) MSE, University of Michigan (1997) BSE in Engineering, KAIST (1994) His research interests emphasize data-driven decision-making in supply chains, dynamic pricing models, and collaborative strategies. Notable contributions include work on subsidy policies for innovation, capacity investment collaboration, and pandemic control through multi-model integration. He leads the Supply Chain Consulting Studio, guiding over 70 projects with companies such as Amazon, Google, and General Motors. Teaching and Awards: Six teaching excellence awards (student-voted) and the 2019 Ross Researcher of the Year Award highlight his dual impact in education and research. His executive education focuses on digital transformation and business analytics. Key Projects: Consulting for 70+ companies across sectors Founder of Ross MSCM's Supply Chain Consulting Studio

David LaiView profile

Associate Professor

• Operations Research
• Logistics Optimization
• Operations Management
• +3 more

Dr. David Lai is an Associate Professor of Operations Management at Queen Mary University of London (QMUL), affiliated with the School of Business and Management and the Department of Business Analytics and Applied Economics. He holds a PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong (2014). Before joining QMUL, he served as Assistant Professor at the University of Southampton (2022–2024), Eindhoven University of Technology (2020–2022), and VU Amsterdam (2014–2020). His research focuses on optimization challenges in logistics, transportation systems, and operations management, including vehicle routing problems, scheduling, and heuristic algorithm development. Key interests include dynamic routing under stochastic conditions, green logistics, and real-time rescheduling for public transit. Dr. Lai’s work spans theoretical contributions (e.g., tabu search heuristics, graph-based formulations) and applied studies (e.g., construction industry logistics, public transport disruption management). His publications highlight innovations in metaheuristics, multi-objective optimization, and network design. He currently holds no explicitly listed scientific awards but has a robust academic portfolio with over 15 peer-reviewed articles since 2009. His teaching and supervision focus on operations management and analytics, though specific advisee names are not documented here.

Zhen ChenView profile

Lecturer

• Cash-Flow Inventory Management
• Stochastic Programming
• Mathematical Modeling
• +3 more

Dr. Zhen Chen is a Lecturer in Operations and Supply Chain Management at Brunel Business School, Brunel University London. He previously held a lectureship at Southwest University, China. He earned his PhD in Management Science and Engineering from Beihang University and was a visiting scholar at the University of Edinburgh. Research Interests: His primary research focuses on cash-flow inventory management using mathematical modeling and stochastic programming. Additional interests include traditional inventory optimization, routing problems, and supply chain management. His work integrates operations research with financial constraints. Publication Trends: Recent articles (2019-2024) consistently address inventory optimization under financial constraints (cash flow, credit loans) using stochastic programming. Key themes include dynamic lot-sizing, service level constraints, and multi-period inventory systems. Technical Skills: Proficient in Python, Java, C++, MATLAB, CPLEX/Gurobi optimization, and LaTeX.

Ziv KatalanView profile

Adjunct Professor

• Operations Management
• Supply Chain Management
• Production Systems
• +4 more

Ziv Katalan serves as Adjunct Professor in the Operations, Information and Decisions department at the University of Pennsylvania's Wharton School and Managing Director for Wharton Global Initiatives. He holds a PhD in Management Science/Operations Research from Columbia University (1995) and a BS in Mathematics from Tel-Aviv University (1987). His educational background includes: BS in Mathematics, Tel-Aviv University (1987) PhD in Management Science/Operations Research, Columbia University (1995) Dr. Katalan's research focuses on optimizing production and service systems through operations research methodologies, specifically examining resource allocation dynamics, scheduling under uncertainty, and manufacturing performance impacts of product variety expansion. His work bridges theoretical modeling with practical applications in supply chain and service operations management. His publications (1994-2005) in Operations Research, Management Science, and Queueing Systems reveal consistent themes: stochastic modeling of production-inventory systems, economic lot scheduling under demand variability, and queueing network analysis for multi-class service systems. A significant portion addresses base-stock policy optimization across rental fleets, manufacturing lines, and polling systems. He has received multiple teaching honors: Wharton MBA Program Core Teaching Award (2013) Wharton MBA Program for Executives Elective Teaching Award (2006, 2011) MBA Core Curriculum Cluster Teaching Award (1997, 1999, 2001) First Place Student Paper Award, ORSA Technical Section (1994) Honorable Mention, George E. Nicholson Competition (1994) Dr. Katalan has taught business analytics, operations management, and quantitative finance across Wharton's MBA programs and Penn's Executive Master’s in Technology Management (EMTM). As EMTM Co-Director (2002-2007), he led this engineering-business joint program. His industry-focused research demonstrates strong connections between theoretical operations models and real-world business applications, particularly in resource-constrained environments.

Fikri KaraesmenView profile

Professor

• Stochastic Modeling
• Operations Research
• Production Systems
• +2 more

Fikri Karaesmen is a Professor in the Department of Industrial Engineering at Koc University. His research focuses on stochastic modeling and operations research, particularly in production, inventory, and service systems. He has published extensively on topics like machine learning integration in inventory control, financial hedging strategies, and strategic customer behavior in service systems. PhD, Northeastern University (1996) MSc, Northeastern University (1992) BS, Middle East Technical University (1990) His work combines mathematical modeling with data-driven approaches, addressing challenges in semiconductor production planning, dynamic pricing under uncertainty, and risk management in inventory systems. Recent publications emphasize machine learning applications in production control and pricing policies for heterogeneous quality products. Selected awards include the TÜBİTAK Incentive Award (2009) and the TÜBA Outstanding Young Scientists Award (2007) . His research has appeared in top journals like IEEE Transactions on Automation Science and Engineering and explores intersections between operations management and financial engineering.

Christian AlmederView profile

Professor

• Supply Chain Management
• Operations Research
• Production Planning and Scheduling
• +3 more

Prof. Dr. Christian Almeder serves as Professor and Head of the Chair of Supply Chain Management within the Faculty of Business Administration and Economics at Viadrina European University (Frankfurt (Oder), Germany). His research focuses on operations research applications in production planning, logistics, and supply chain optimization, with particular expertise in lot sizing, scheduling, and perishable goods management. He maintains active research output with publications spanning from 1997 to 2023. Almeder's research centers on mathematical modeling of complex production and logistics systems. His primary contributions involve developing heuristic and metaheuristic solutions for capacitated lot sizing problems, multi-level scheduling, and integrated production-distribution planning. Key specialties include handling perishability constraints, lead time uncertainties, and batch processing requirements using genetic programming, simulation-based optimization, and clearing function approaches. His work bridges theoretical operations research with industrial applications in supply chain management. Analysis of his 15 most recent publications (2013-2023) reveals a consistent focus on lot sizing and scheduling, with increasing emphasis on integrated supply chain problems and perishable goods logistics. Methodologically, he combines metaheuristics (genetic programming, simulated annealing) with simulation techniques to address real-world complexities like stochastic processing times and limited buffers. His work demonstrates strong application in production planning parameter tuning, vehicle routing integration, and robust operational planning under uncertainty.

• Operations Management
• Supply Chain Management
• Inventory Management
• +8 more

Suresh Chand is a Professor and the Louis A. Weil Jr. Chair of Management at the Daniels School of Business, Purdue University . He serves as Department Head of Supply Chain and Operations Management. Ph.D., Industrial Administration, Carnegie Mellon (1979) M.S., Industrial Engineering, University of Texas (1976) M. Tech. & B. Tech., Mechanical Engineering, IIT Kanpur (1974, 1972) His research focuses on production process optimization across manufacturing and healthcare sectors. Key areas include: Capacity and production planning for volume flexibility Supply chain modeling to align supply with demand Reduction of patient flow time in healthcare systems Learning/forgetting effects in scheduling and setups Statistical process control and inventory management Professor Chand has published over 50 articles in Operations Research , Management Science , and similar journals. His work spans theoretical advancements in lot sizing, scheduling algorithms, and practical applications in healthcare and global supply chains. He has served as Associate Editor for Management Science (1986-2008), Area Editor for Production and Operations Management (1992-2003), and Senior Editor for Manufacturing and Service Operations Management (1999-2004). He was General Chair for the POM 2005 international conference. Professor Chand teaches core and elective courses in Operations Management to MBA, undergraduate, and doctoral students. He has taught at Purdue's Hannover campus and led Summer Study Abroad programs at TVS Motors in India.

• Operations Research
• Mathematical Programming
• Management Science
• +2 more

Edoardo Fadda is a Fixed-term tenure-track Assistant Professor at the Department of Mathematical Sciences (DISMA), Politecnico di Torino . He serves as a member of the College of Mathematical Engineering and College of Electronic, Telecommunications and Physics Engineering . Specializes in Operations Research and Mathematical Programming Active in stochastic optimization , reinforcement learning , and control applications Teaching roles include Optimization Methods for Control Applications and Stochastic Programming courses His research spans supply chain optimization , logistics , and AI-integrated decision systems , focusing on uncertainty modeling and multi-stage stochastic programming. He leads the Development of Decision Support Systems and the SUPERSONIC project for ecological logistics, alongside commercial consulting for RIDIX SPA through Fondimpresa contracts. Notable collaborations include Paolo Brandimarte and Francesca Maggioni . Edoardo supervises PhD candidates Alessia De Crescenzo (39th cycle) and Lorenzo Mazza (40th cycle). His publications emphasize stochastic customer behavior , perishable product policies , and kernel-based system identification , with applications in aerospace, smart cities, and industrial manufacturing.

Thomas Welsh ArchibaldView profile

Professor

• Operations Management
• Stochastic Dynamic Programming
• Inventory Management
• +5 more

Thomas Welsh Archibald serves as Professor of Business Modelling and Director of Research at the University of Edinburgh's Business School within the Management Science and Business Economics department. His academic career spans decades with deep expertise in operations research and stochastic modeling for complex business systems. Education: BSc from University of Edinburgh PhD from University of Edinburgh Professor Archibald's research integrates stochastic dynamic programming with practical business applications across multiple domains. His primary focus areas include inventory management for perishable goods and multilocation systems, asset management for infrastructure networks, and strategic decision-making under uncertainty. He develops sophisticated mathematical models addressing water reservoir operations, supply chain resilience, and startup operational policies, frequently employing Markov decision processes and stochastic optimization frameworks. His recent publications (2022-2024) reveal a strategic shift toward financial-operations integration, examining cash flow constraints in inventory systems, competitive dynamics in omnichannel retail, and strategic consumer behavior in luxury markets. These works demonstrate his consistent application of stochastic modeling to bridge theoretical operations research with real-world business challenges, particularly in volatile markets and emerging industries. Scientific Recognition: Recipient of two major research prizes (specific awards not detailed in source) Professor Archibald has secured significant research funding supporting five major projects and supervised one graduate student. His grant portfolio reflects strong industry-academia collaboration, particularly with financial institutions through the Credit Research Centre. As Director of Research, he shapes strategic research directions across the Business School while maintaining active industry engagement. He contributes to interdisciplinary initiatives including the Edinburgh Strategic Resilience Initiative, where his expertise in stochastic modeling informs climate adaptation strategies for infrastructure, and the Credit Research Centre where he develops risk assessment frameworks for financial systems.

Leyuan ShiView profile

Professor

• Complex Systems Optimization
• Supply Chain Networks
• Manufacturing Systems
• +5 more

Prof. Leyuan Shi is a Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. Her primary affiliation is with the College of Engineering, and she holds additional affiliations with the Manufacturing Systems Engineering Program. Her research focuses on developing theory and methodology for designing and optimizing complex systems, including supply chain networks, manufacturing systems, and communication networks. Her work spans three key areas: semantic modeling/design of systems, sensitivity analysis via discrete-event simulation, and control/optimization frameworks. Her research interests include scheduling optimization, robust optimization, simulation-based decision-making, and applications in healthcare logistics (e.g., radiation therapy planning) and semiconductor manufacturing. She has contributed significantly to methods like the nested partitions algorithm and evolutionary heuristics for solving challenging scheduling problems. Recent publications emphasize optimization in multi-stage production systems, dynamic sampling for feasibility determination, and integration of production and transportation scheduling. Her work bridges theoretical advancements with real-world applications in manufacturing, healthcare, and emergency logistics planning. Her expertise spans algorithm design, stochastic systems, and complex system modeling. Prof. Shi’s research also addresses practical challenges such as wafer defect inspection optimization, machine learning in treatment planning, and emergency material distribution strategies under uncertainty. She collaborates across disciplines to tackle large-scale optimization problems in both academic and industrial contexts.