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OR56 Stream - Metaheuristics

Stream Organiser

Ender Özcan
(more information)


Andrew Parkes
(more information)

Email: ajp@Cs.Nott.AC.UK


Stream Definition

We invite abstracts and presentations, either theory or practice-oriented (preferably on real world applications) that discuss any of the issues of:

  • Meta-heuristics
  • Systems to build systems, particularly (meta/hyper-)heuristics.
  • Developing the analytical /theoretical understanding of (meta/hyper-)heuristics.

We are particularly interested in:

  • Analyses that lead to some insight into the behaviour of one or more meta-heuristics. For example, but not limited to, landscape analysis, stochastic analysis methods or modeling.
  • Methods that are based on machine learning and/or allow a more general use of meta-heuristics and heuristics. For example, hyper-heuristics or adaptive search control systems.

Please do not hesitate to contact us directly if you are unsure as to whether a particular topic would be appropriate.


Ender Özcan

Ender Özcan is a lecturer in Operational Research and Computer Science with the Automated Scheduling, Optimisation and Planning (ASAP) research group in the School of Computer Science at the University of Nottingham, UK. He received his PhD from the Department of Computer and Information Science at Syracuse University, NY, USA in 1998. He worked as a lecturer in the Department of Computer Engineering at Yeditepe University, Istanbul, Turkey from 1998-2007. He established and led the ARTIficial Intelligence research group from 2002. He served as the Deputy Head of the Department from 2004-2007. Dr Özcan joined the ASAP group as a senior research fellow in 2008. He has been serving as an executive committee member for the LANCS initiative, which is one of the largest Science and Innovation Rewards given by EPSRC (Engineering and Physical Sciences Research Council, UK). His main research interests include intelligent decision support systems, search and optimisation using heuristics, hyper-heuristics, meta-heuristics, hybrid approaches and their theoretical foundations, and their applications to the real world and theoretical problems.

Andrew Parkes

Andrew Parkes obtained a Ph.D. in theoretical physics in 1984 from King's College of the University of London. He then held research positions at the University of Southampton, CERN (the particle physics accelerator and research laboratory at Geneva, Switzerland), the University of California at Davis, USA, and the ETH in Zurich, Switzerland. In 1993 he changed from Physics to Artificial Intelligence and Computer Science. In 1999 he obtained a Ph.D., in Computer Science from the University of Oregon, USA, He became a faculty member of the Computational Intelligence Research Laboratory at the University of Oregon working on topics in combinatorial optimisation. In 2005 he joined the Automated Scheduling, Optimisation and Planning Research Group (ASAP) within the School of Computer Science of the University of Nottingham where he researched the management and planning of teaching space facilities within educational institutions. Since 2008 he has been a Lecturer in Operational Research and Computer Science at the University of Nottingham with particular responsibility to support the recent EPSRC-funded Science and Innovation award for "The LANCS Initiative: An initiative to build and maintain national research capacity in foundational Operational Research." He is a member of the LANCS executive committee and also coordinating a research cluster into the understanding of heuristics. He was on the organising committee for the 2007 International Timetabling competition. He is a co- inventor on two patents and has many refereed international publications.


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