Professor Djamila Ouelhadj
I am a Senior Lecturer in Operational Research and a member of the Logistics and Operational Research Group (LORG) in the Department of Mathematics at the University of Portsmouth. I am also the Course Leader of MSc Logistics and Supply Chain Management.
My main research interests are Operational Research and the development of novel mathematical optimisation models, advanced meta-heuristic methods, and intelligent decision support systems for automatically producing high quality solutions to a wide range of real world optimisation, scheduling and logistics problems. Real world problems include: manufacturing, healthcare, personal scheduling, vehicle routing and transportation, supply chain and production management, sustainability and renewable energy, etc.
I have carried out successful research in Operational Research since 1995. I received my PhD from the University of Nottingham. I then worked as a researcher and a lecturer for six years in the Automated Scheduling, Optimisation and Planning Research group (ASAP) at the University of Nottingham. I have chaired the scheduling stream in OR53, OR54, and OR55. I have organised several Southern Operational Society Workshops on Optimisation and Scheduling in healthcare, and Logistics and Transportation.
I am a co-investigator on several EU grants: SEABILLA which entailed applying Operational Research methodologies to sea-border security, 2OM and LEANWIND that involve the application of Operational Research methodologies to optimise the operations and maintenance procedures of offshore wind farms. I am also a co-investigator on several Technology Strategy Board (TSB) grants, and the principal investigator on a Higher Education Investment Framework (HEIF) funded project to launch an Operational Research centre at the University of Portsmouth.
I am the Southern Regional Representative to the General Council of the Operational Research Society and a member of the Operational Research Society, UK.
- Automated optimisation and scheduling
- Heuristics, meta-heuristics, and hyper-heuristics for combinatorial optimisation and scheduling problems: Exploration and development of heuristics, meta-heuristics, hyper-heuristics, evolutionary algorithms, and multi-objective methods to solve complex real world optimisation, scheduling, and Logistics problems. Examples of applications: Manufacturing, Timetabling, Nurse Rostering, Vehicle Routing, Grid Computing, Robotics, etc.
- Cooperative and parallel search methodologies: cooperative and parallel meta-heuristics and hyper-heuristics
- Agent-based scheduling
- Intelligent decision support systems
- Multi-agent systems and software agents
- Applications: Logistics, Transportation and vehicle routing, Supply Chain Management, Inventory Management, Manufacturing and Production Scheduling, Healthcare, Renewable Energy and Sustainability