جست‌وجوی استاد و پژوهشگر

Andreas Kloseمشاهده پروفایل

دانشیار

• Operations Research
• Combinatorial Optimization
• Integer Programming
• +۳ مورد دیگر

Andreas Klose is an Associate Professor at the Department of Mathematics, Aarhus University, Faculty of Science. His work focuses on combinatorial optimization and integer programming, particularly for logistics applications. Active in exact solution approaches for bi-objective and uncertain facility location problems Develops metaheuristics for fixed charge transportation challenges Teaches master courses on location planning, vehicle routing, and optimization methods Research Trends: Recent publications emphasize facility location under uncertainty, exact algorithms for capacitated problems, and metaheuristic approaches. Topics span both theoretical and applied operations research. Teaching: Offers courses on Multiple Criteria Optimization , Location Planning , Vehicle Routing , and Metaheuristics , alternating between fall and spring semesters. Collaborations: Frequently collaborates with researchers like Simon Gadegaard and Kim Jörnsten on facility location and transportation problem frameworks.

Thomas Jacob Riis Stidsenمشاهده پروفایل

دانشیار

• Operations Research
• Mathematical Modelling
• Optimization Algorithms
• +۲ مورد دیگر

Dr. Thomas Jacob Riis Stidsen is an Associate Professor in the Department of Technology, Management and Economics at the Technical University of Denmark. His research specializes in operations research methodologies applied to industrial planning problems, including mathematical modeling, decomposition algorithms, and metaheuristic optimization techniques. His expertise spans operations research, mathematical modeling, optimization algorithms, educational timetabling, and telecommunications optimization. He develops practical solutions for scheduling, resource allocation, and planning systems across education, healthcare, and production sectors. Research outputs from 2022-2025 focus heavily on educational timetabling optimization, featuring novel algorithms for school and examination scheduling. Recent publications demonstrate strong emphasis on mixed integer programming and metaheuristic approaches to complex scheduling challenges in real-world contexts. Stidsen has received recognition for his contributions to timetabling research, including winning the International Timetabling Competition 2019. His work bridges theoretical operations research with practical implementation in educational and healthcare systems.

• Operations Research
• Logistics Optimization
• Heuristic Algorithms
• +۳ مورد دیگر

Associate Professor Dario Pacino is affiliated with the Technical University of Denmark (DTU), specifically within the Department of Technology, Management and Economics under the Operations Research Section. His research focuses on optimization challenges in logistics and transportation systems, including container stowage planning, berth allocation, and the application of AI techniques like reinforcement learning. He holds a position at DTU's Management Science Division and is based in Lyngby, Denmark. His work emphasizes heuristic and metaheuristic algorithms for solving complex logistics problems. Notable areas include Roll-on/Roll-off (RoRo) ship stowage planning, dynamic berth allocation, and discrete event simulation for healthcare logistics. He has contributed to mathematical models addressing draft limits in shipping and stochastic fleet optimization for urban mobility. Publications from 2022 onward highlight advancements in reinforcement learning integration with traditional operations research methods, demonstrating a trend toward AI-driven logistics solutions. His work bridges theoretical optimization with practical applications in maritime and healthcare sectors. No scientific awards are explicitly listed in the provided text. His advising and grants sections remain unspecified, though his research collaborations are evident through multi-institutional projects. He is part of the Operations Research Section's research team, focusing on decision support systems and optimization under uncertainty.

Rune Møller Jensenمشاهده پروفایل

دانشیار

• Container Vessel Stowage Planning
• Operations Research
• Optimization Methods (Metaheuristics, Constraint Programming)
• +۳ مورد دیگر

Rune Møller Jensen is an Associate Professor in Data Science and Head of The Maritime Hub at the IT University of Copenhagen. He specializes in container vessel stowage planning optimization, with expertise in metaheuristics, constraint programming, and mathematical programming. His work bridges academia and industry through projects like churn prediction and AIS-based ETA forecasting. He co-founded Sealytix, a leading stowage analytics firm, and previously led Optivation until 2022. Jensen holds awards including the Hede Nielsen Prize (2005) and The McKinsey Award (1998). Education: Studied Symbolic AI at Carnegie Mellon University (CMU). Research focuses on optimizing maritime logistics, energy-efficient transportation, and decision support systems for liner shipping. Key projects include Greenship (2014-2016), REALCAP (2016-2018), and BAYSTOW (2008-2012). Media engagements include discussions on AI ethics and industry collaboration. His research portfolio spans 86 publications and 10+ projects, emphasizing optimization algorithms and real-world maritime applications. As head of The Maritime Hub, he supports emerging researchers through interdisciplinary initiatives.

Marco Chiarandiniمشاهده پروفایل

دانشیار

• Operations Research
• Optimization Algorithms
• Integer Programming
• +۱۰ مورد دیگر

Marco Chiarandini is an Associate Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), with a secondary affiliation to the SDU Climate Cluster. His research focuses on Operations Research, Optimization Algorithms, and their applications in domains such as transportation, healthcare, and education. He has led or contributed to projects addressing dynamic traffic estimation, dementia care app design, and sustainable software development. Chiarandini has supervised students including P. Tampakis and C. McCarthy, and his work has been featured in interdisciplinary collaborations with institutions globally. His recent articles explore topics like goal-scoring prediction in football and urban traffic modeling, reflecting his expertise in data science and algorithmic design. His academic contributions span over 50 publications, emphasizing methodological advancements in optimization and heuristic algorithms. He actively participates in conferences and peer review, and has coordinated EU-funded projects like Data Science for University Management (2019–2023). Chiarandini’s teaching includes courses on linear programming and metaheuristics, integrating practical applications with theoretical foundations.