جستجوی استاد راهنمای دانشگاهی

Axel Parmentierمشاهده پروفایل

مدرس

• Operations Research
• Machine Learning
• Data-Driven Optimization
• +۵ مورد دیگر

Axel Parmentier is a Lecturer and researcher at the École Nationale des Ponts et Chaussées, where he founded the AI for Air Transport industry research chair with Air France. His work focuses on the intersection of operations research and machine learning, particularly in data-driven combinatorial optimization and stochastic optimization, with industrial applications in air transportation, supply chain, and predictive maintenance. He holds a Ph.D. and has been recognized with awards including the AMIES Dissertation Award (2017) for applied mathematics with industrial impact and the Robert Faure Prize (under 35) from ROADEF. His research also includes contributions to structured reinforcement learning, optimization layers in machine learning, and explainable AI for operational decisions. Awards: AMIES Dissertation Award, Robert Faure Prize Labs/Teams: CERMICS laboratory, AI for Air Transport Chair (collaboration with Air France) Grants/Projects: Continent-scale inventory routing solutions, Renault’s logistics optimization His advising includes students like Victor Cohen, whose work on predictive maintenance was featured on France Culture.

• Operations Research
• Logistics
• Supply Chain Management
• +۳ مورد دیگر

Remy Dupas is a Professor at the University of Bordeaux , affiliated with the IMS Bordeaux - Integration, Material to System Laboratory within the Production Engineering research group. His work focuses on Operations Research , Logistics , and Transportation Systems , developing advanced algorithms for complex routing and supply chain optimization problems. Research Highlights: Innovative Branch-Cut-and-Price algorithms for Two-Echelon Vehicle Routing Problems with drones and time windows City Logistics models for sustainable urban freight distribution in Tokyo MultiAgent Systems for supply chain coordination 3D Loading Constraints integration in pickup-and-delivery problem solving Rail-Rail Transshipment scheduling methodologies Key Publications (2024-2007) demonstrate expertise in Combinatorial Optimization , Dynamic Routing , and Interoperability Metrics for enterprise systems. His research is characterized by strong Algorithm Development and Real-Time Transportation solutions.

Muhammad Khakim Habibiمشاهده پروفایل

استادیار

• Supply Chain Management
• Operations Research
• Logistics Optimization
• +۴ مورد دیگر

Dr. Muhammad Khakim Habibi is an Assistant Professor in the Supply Chain Management & Information Systems Academic Area at Rennes School of Business. His research focuses on optimizing supply chain networks, stochastic problems in logistics, and sustainable closed-loop systems. He holds a Ph.D. in Industrial Engineering from École des Mines de Saint-Étienne (2017), preceded by master's degrees in Industrial Engineering and Supply Chain Engineering from French and Indonesian institutions. Teaches courses including Supply Chain Analytics , Optimization and Simulation , and Machine Learning in Supply Chain . Research emphasizes reverse supply chain design , hub location problems , and stochastic modeling . His work has been published in journals like International Journal of Production Economics and International Journal of Production Research . He serves as a reviewer for top-tier journals and has presented at conferences such as EURO and IFAC. Professional affiliations include ROADEF, EurOMA, and POMS.

Evren Sahinمشاهده پروفایل

پژوهشگر

• Operations Management
• Supply Chain Optimization
• Healthcare Logistics
• +۴ مورد دیگر

Evren Sahin is a researcher specializing in Operations Management with a focus on Supply Chain Optimization , Healthcare Logistics , and Inventory Management . He is affiliated with the Industrial Engineering Laboratory, where his work integrates optimization , discrete event simulation , and production systems . His research explores the intersection of emergency vehicle logistics , home healthcare operations , and agri-food supply chains . Recent publications highlight applications of machine learning in demand forecasting and digital twin technology for supply chain agility. Collaborations with Zied Jemai, Yves Dallery, and Andrea Matta span theoretical and applied projects. Key methodologies include integer programming , inventory control models , and human-robot kitting systems . His work addresses closed-loop supply chains , perishable product management , and emergency medical service improvements through simulation and optimization.

Cyril Allignolمشاهده پروفایل

مدرس

• Combinatorial optimization
• Metaheuristics
• Semantics of languages
• +۴ مورد دیگر

Cyril Allignol is a Lecturer and Researcher in the OPTIM team at the National School of Civil Aviation (ENAC) research laboratory. His work focuses on two primary themes: (1) solving combinatorial optimization problems related to air traffic and airport operations using constraint programming , and (2) formalizing reactive languages to ensure guaranteed properties for air traffic control and piloting assistance tools. PhD in Computer Science and Telecommunications (2011) from the University of Toulouse ENAC Engineer (2006) Master's in Computer Science and Telecommunications (2006) from the University of Toulouse His research spans air traffic conflict resolution , detect-and-avoid algorithms for UAVs/UAS , and formal methods in reactive language compilation . He has contributed to constraint programming frameworks, robust gate allocation models, and 3D trajectory deconfliction systems. His work integrates metaheuristics , geometrical algorithms , and formal verification techniques. Publications reveal expertise in mathematical optimization , UAS integration , and bigraph-based modeling for avionics systems. He collaborates with institutions across France, Italy, Georgia, and the United States through conferences like ICRAT , ATM Seminar , and ROADEF . His team affiliation ( OPTIM ) and technical focus on conflict resolution , self-separation , and navigation accuracy highlight his contributions to air traffic safety and efficiency . Current projects include 4D-trajectory deconfliction and formal methods for avionics software .

• Operations Research
• Logistics Optimization
• Supply Chain Management
• +۳ مورد دیگر

Yuanyuan Li is a Researcher at LINKS Foundation and currently pursuing a PhD in Operations Research and Management at ESSEC Business School (France) with a visiting PhD at Nanyang Business School (Singapore). She holds a Master’s in Software Engineering and a Bachelor’s in Computer Engineering from the Polytechnic University of Turin (Italy). Her research focuses on optimization techniques for sequential decision-making, large-scale optimization problems, and their applications in last-mile delivery and startup operations. She has presented work at prestigious conferences including INFORMS Annual Meeting, POMS, and EURO, and contributed to EU-funded projects like LEXIS and SYNCHRO-NET. Technical skills include programming languages (Java, Python, OPL, C, SQL, HTML), software tools (CPLEX, Gurobi, Eclipse, MySQL), and operating systems (Windows, macOS, Linux). Language proficiency includes Chinese (native), English (fluent), and Italian/French (basic).

• Operations Research
• Vehicle Routing Problems
• Graph Coloring
• +۲ مورد دیگر

Daniel Porumbel is an Associate Professor with expertise in operations research and combinatorial optimization. His research focuses on developing algorithms for complex routing problems under uncertainty, particularly capacitated vehicle routing with evidential demands. Key research areas include belief function theory, permutation set-covering problems, and efficient lower bound techniques for routing and location problems. Research Interests: Optimization under uncertainty using evidential demands Column generation and local search metaheuristics Dual feasible functions for routing optimization

• Healthcare Logistics
• Operations Research
• Supply Chain Optimization
• +۳ مورد دیگر

Issam NOUAOURI is an Associate Professor with HDR (Habilitation à Diriger des Recherches) specializing in healthcare logistics, operations research, and disaster management. His research focuses on optimizing patient flows, material resources, and supply chain networks in dynamic and uncertain environments. Key areas include emergency medical services, sustainable supply chains, and AI-driven healthcare solutions. Education: Ph.D. Thesis: 'Gestion hospitalière en situation d’exception: optimisation des ressources critiques' (2006-2010) HDR: 'Contribution à l’optimisation des flux de patients et matières dans un environnement incertain et dynamique' (2023) Research interests span healthcare logistics, optimization algorithms (metaheuristics, genetic algorithms), disaster response planning, and sustainable supply chain design. Notable work includes modeling ambulance routing, emergency department resource allocation, and collaborative hospital networks. Publications emphasize practical applications in healthcare systems, such as reducing patient waiting times, optimizing vehicle routing for hazardous waste, and integrating AI in disease diagnosis. His work bridges theoretical optimization and real-world healthcare challenges. Grants and collaborations include projects on hospital logistics within Groupements Hospitaliers de Territoire (GHT), disaster management systems, and rail safety co-simulation. He has supervised seven Ph.D. students focusing on healthcare scheduling, supply chain optimization, and hyperheuristics. Labs/Teams: Active contributor to the LGI2A laboratory, focusing on interdisciplinary research in intelligent systems and healthcare operations.

Frédéric PICHONمشاهده پروفایل

استاد

• Uncertain Reasoning
• Information Fusion
• Machine Learning
• +۳ مورد دیگر

Frédéric Pichon is a Full Professor at Artois University's Laboratory of Computer Engineering and Automation of Artois (LGI2A), part of the Faculty of Applied Sciences in Béthune, France. He holds a Ph.D. in Information and Communication Systems (2009) and an H.D.R. (2018) from Artois University. His research focuses on uncertain reasoning, information fusion (particularly belief functions theory), and machine learning applications in decision-making under uncertainty. Education: B.Eng. (Hons) in Computer Networks and Distributed Systems, Edinburgh Napier University, 2003 M.Sc. in Information Technology, Aalborg University Esbjerg, 2005 Ph.D., University of Technology of Compiègne, 2009 H.D.R., Artois University, 2018 Research Interests: Belief functions theory and applications Optimization under severe uncertainty Machine learning with uncertain data Information fusion for decision support Articles Trends: Recent work emphasizes belief function-based solutions for optimization problems (e.g., shortest path, vehicle routing) and deep learning integration with uncertainty quantification. Early-career contributions include foundational work on Dempster-Shafer theory and conflict analysis. Awards: Notable recognitions include the IJAR Early Career Researcher Award (2022), multiple best paper awards at LFA and BELIEF conferences, and distinctions for student research supervision. Advising & Grants: Supervised 9 PhD students (3 in progress). Active in organizing international conferences (BELIEF, LFA) and editorial roles (Area Editor for International Journal of Approximate Reasoning). Research spans theoretical advancements and applied projects in logistics, image processing, and simulation. Labs/Teams: Core member of LGI2A, collaborating with institutions like Heudiasyc and IBISC labs on uncertainty modeling and fusion systems.

• Industrial Engineering
• Operations Research
• Data Analysis
• +۵ مورد دیگر

Dr. Anne LOUIS is a Research Director at CESI, leading the application domain of 'Industry of the Future' and heading the Research & Innovation Department for CESI Nord-Ouest. She holds an HDR in Electronics from the University of Rouen (2006) and a PhD in Microwaves from the University of Limoges (1998). Her work focuses on decision support systems for industrial tasks, predictive maintenance analytics, and Industry 5.0 demonstrators. She leads a research platform on industrial performance (2015–2020) and manages a team in Engineering and Numerical Tools. Research Interests: Decision support tools for task scheduling, maintenance operations analysis, and multi-agent systems for industrial systems. Current Programs: Industry 5.0 demonstrator development and industrial performance platforms. Her research spans robotics optimization in horticulture, bio-waste management systems, and SME open innovation strategies. She supervises four ongoing PhD projects on AI-driven maintenance, multimodal transport supervision, and open innovation sustainability. Completed theses include robotic task optimization (2022), bio-waste treatment (2021), and SME innovation practices (2021). Scientific Leadership: Member of LINEACT Scientific Council, COMUE Normandie's Numerical Sciences pole, and doctoral school committees. Over 25+ publications since 2018, focusing on optimization algorithms, multi-agent simulations, and innovation frameworks.

• Combinatorial Optimization
• Applied Mathematics
• Integer Linear Programming
• +۳ مورد دیگر

Diego DELLE DONNE is an Assistant Professor (tenure-track) at ESSEC Business School in Paris, France, within the Information Systems, Data Analytics and Operations department. He holds a PhD in Computer Science from the University of Buenos Aires (2016), along with earlier degrees from the same institution. Prior to his current role, he held post-doctoral positions at ESSEC, École Polytechnique, and Sorbonne Paris Nord University. His research focuses on combinatorial optimization, applied mathematics, and their real-world applications in logistics, urban planning, and resource management. Education: PhD in Computer Science, University of Buenos Aires (2016) MSc in Computer Science, University of Buenos Aires (2009) BSc in Computer Science, University of Buenos Aires (2008) Research Interests: His work emphasizes optimization algorithms for sustainable urban logistics, such as integrating public transport for last-mile deliveries to reduce CO2 emissions, and integer linear programming applications in hydrocarbon field planning, waste management, and salmon farm operations. He also explores theoretical challenges in graph coloring, polyhedral studies, and sparse approximation techniques. Recent Article Trends: Recent publications highlight advancements in column generation methods for multi-echelon delivery systems, branch-and-price algorithms for clustering and coloring problems, and strategic planning for freight integration with public transit. His work bridges theoretical optimization with practical urban and industrial challenges, emphasizing sustainability and efficiency. Advising & Grants: He has supervised multiple master’s theses, including works on leaf collection optimization and logistics routing. While specific grant details are not detailed, his research projects reflect collaboration with industry partners like petroleum companies in Argentina and urban management initiatives. Labs/Teams: His current project focuses on leveraging public transport’s excess capacity for urban parcel delivery, part of broader efforts to enhance sustainable logistics through mixed-integer programming and operational research techniques.

• Operational Research
• Artificial Intelligence
• Algorithms
• +۳ مورد دیگر

Simon Caillard is a Researcher-Lecturer at CESI, affiliated with the Department of Informatics. His research focuses on operational research and artificial intelligence, particularly in healthcare training optimization, vehicle routing problems, and scheduling algorithms. He holds a Master's in Computer Systems and Networks Engineering (2017) and a PhD in Informatics and Operational Research (2021), both from the University of Picardie Jules Verne – Amiens. His educational activities include teaching Informatics/Computer Sciences, covering algorithms and databases, to Engineers in 1st and 2nd years, and Masters programs. Research interests include developing metaheuristics like Ant Colony Systems for healthcare simulation training and logistics optimization. His work bridges theoretical models with real-world applications in healthcare resource allocation and sustainable mobility solutions. Key contributions include algorithms addressing dynamic electric vehicle routing and energy-efficient manufacturing. He contributed to the Green-JIT² project (2022) and organized the AlsaceTech Spring School on AI (2022-2023). His publications span journals and conferences, with a focus on optimization techniques for healthcare and industrial systems. As part of the Engineering and Numerical Tools research team, he collaborates on projects integrating computational methods for practical challenges in healthcare and logistics.

Fabien LEHUEDEمشاهده پروفایل

استاد

• Logistics
• Operations Research
• Transportation Systems
• +۳ مورد دیگر

Fabien LEHUEDE is a Professor and Head of the Optimization and Decision Support group at the Département Automatique, Productique et Informatique (DAPI) at IMT Atlantique. He is affiliated with the Modelis research team within the Nantes Digital Sciences Laboratory (LS2N) and co-hosts the LS2N's vehicles and mobility theme. His research focuses on logistics optimization, transportation networks, and vehicle routing, with a strong emphasis on advanced operations research methods. His work addresses challenges in freight transportation scheduling, service network design, and robust optimization. He collaborates internationally, contributing to both theoretical advancements and practical applications in supply chain management and urban logistics. Key techniques in his research include integer programming, column generation, and large neighborhood search algorithms. Recent publications highlight his contributions to continuous-time service network design, park-and-loop routing, and time-consistent dial-a-ride problems. His research bridges academic and industrial needs, with applications in healthcare logistics and multi-echelon distribution systems.

Lionel AMODEOمشاهده پروفایل

استاد

• Operations Research
• Supply Chain Management
• Inventory Management
• +۳ مورد دیگر

Lionel Amodeo is a Professor and Director of the Computer Science and Digital Society Laboratory at the University of Technology of Troyes (UTT), leading a team of 170 members since 2021. He has held multiple leadership roles, including Head of the Industrial System Optimization Laboratory (2018-2020) and Head of Production and Robotics Department (2018-2020). He is a member of the French National Council of Universities (CNU 61) and serves on international committees such as the IFAC Technical Committee TC 7.4 Transportation Systems. His research focuses on Operations Research , Supply Chain Optimization , and Inventory Management , with expertise in meta-heuristics (e.g., Ant Colony, Particle Swarm). He has authored 7 books and over 200 publications, achieving an H-index of 25. His work addresses topics like energy-efficient production systems, disassembly logistics, and hospital logistics optimization. Recent articles emphasize sustainable supply chains, energy efficiency in manufacturing, and healthcare logistics. He has supervised 22 Ph.D. students, including Dr. Hicham Chehade (Best Thesis, Champagne-Ardennes Academy, 2009), and 37 Master’s students. His international collaborations include roles as an invited professor at universities in Mexico, Chile, Colombia, and Brazil. He directs the Industrial Systems Engineer Degree program (300+ students) and chairs the Scientific Council of UTT. His contributions span editorial roles in journals like Journal of Engineering Mathematics and Journal of Modelling and Simulation of Systems .

• Combinatorial Optimization
• Industrial Systems
• Vehicle Routing Problems
• +۳ مورد دیگر

Alice YALAOUI is a Professor at the University of Technology of Troyes (UTT), specializing in optimization of industrial systems and logistics. She serves as Deputy Director of Training and Pedagogy , overseeing educational innovation and new training pathways. She also leads the Industrial Engineering program and manages research themes in logistics and production systems. Education: Doctorate in Systems Optimization (2004, UTT), DEA in Systems Optimization (2001, UTT), Industrial Systems Engineering (2001, UTT). Roles: Deputy Head of Industrial Engineering, CNU 61st Section member, and steering committee member of the Connected Innovation Chair. Research Focus: Modeling and development of combinatorial optimization methods for industrial systems (e.g., scheduling, lot-sizing, vehicle routing). Key areas include production design, warehousing, and logistics optimization. Advising: Supervised 13 PhD/Master’s students since 2006. Active in research networks, including joint teams with UTT-DUT Da Nang (Vietnam). Labs & Teams: Head of the research theme 'Design of Logistics and Production Systems' at LOSI/LIST3N labs. Involved in organizing international conferences like IFAC MIM (2016) and ROADEF (2013).