Overview of the Group
Welcome to the Task Force on Hyper-heuristics within the Technical Committee of Intelligent Systems and Applications at IEEE Computational Intelligence Society.
Hyper-heuristics represent one of the recent emerging meta-heuristics which attracted an increasing amount of research attention. Instead of designing heuristic methods with pre-defined parameters or mechanisms, hyper-heuristics search for or learn the selections or configurations of problem specific 'low level' heuristics which are then employed on the fly to solve the problem in hand. They therefore concern the search space of heuristics rather than solutions themselves. The algorithms are thus self-adaptive, and are able to deal with a much wider range of problems without extensive development effort. In addition to employing search algorithms, the current literature has started to investigate a wider range of computational intelligence and artificial intelligence techniques including constraint satisfaction, decision support, fuzzy rules, knowledge based systems, learning, and many others, aiming to develop advanced hybrid intelligent systems. Due to their self-adaptive nature, hyper-heuristics have been successfully applied within intelligent systems to concern various real world applications including personnel scheduling, job shop scheduling, 2D/3D strip packing, routing, assembly line, timetabling, knapsack and many other complex problems.
Along with the current state-of-the-art Hyper-heuristics research development at the interface of AI, CI and OR, we aim to further promote the scope of both intelligence techniques and applications within advanced hybrid intelligent systems.
Objectives
In addition to promoting the development of hyper-heuristics in research, under the Technical Committee of Intelligent Systems Applications, we also aim to motivate the applications of hyper-heuristics in real world complex and constrained problems.
The research of hyper-heuristics is inherently interdisciplinary, and lies naturally at the interface of Artificial Intelligence, Computational Intelligence and Operational Research. To realise the objectives, we aim to organise a range of activities under the proposed task force and jointly with task forces within other Technical Committees at IEEE Computational Intelligence Society:
- To organise future events including workshops, special sessions and/or tutorials at international conferences
- To organise special issues at international journals in AI, CI and OR
- Facilitate the collaboration between researchers and practitioners in Hyper-heuristics by means of meetings and publications in international journals.
- Contribute to the development of original thinking in Hyper-heuristics.
- Exchange experiences and knowledge, promote critical discussion, and facilitate contacts with researchers and practitioners in this research area.
Chair and Vice Chair (2013-2018)
Chair: Rong Qu, University of Nottingham, UK
Vice-Chair: Nelishia Pillay, University of KwaZulu-Natal, South Africa
Members
- Masri Ayob, Universiti Kebangsaan Malaysia
- Ruibin Bai, University of Nottingham Ningbo, China
- Edmund Burke, Queen Mary University of London, UK
- Patrick De Causmaecker, Katholieke Universiteit Leuven Campus Kortrijk, Belgium
- Nasser Dolayme, Universiti Kebangsaan Malaysia, Malaysia
- Maoguo Gong, Xidian University, China
- Mark Johnston, Victoria University of Wellington, New Zealand
- Edward Keedwell, University of Exeter, UK
- Graham Kendall, University of Nottingham, Malaysia
- Ahmed Kheiri, Lancaster University
- Jingpeng Li, University of Stirling, Scotland
- Mustafa Misir, Nanjing University of Aeronautics and Astronautics, China
- Gabriela Ochoa, University of Stirling, Scotland
- Ender Ozcan, University of Nottingham, UK
- Andrew Parkes, University of Nottingham, UK
- Riccardo Poli, University of Essex, UK
- Said Salhi, University of Kent at Canterbury, UK
- Jerry Swan, University of York, UK
- Greet Vanden Berghe, KAHO Sint-Lieven, Belgium
- John Woodward, University of Stirling, Scotland
- Mengjie Zhang, Victoria University of Wellington, New Zealand
Key Resources
Recent Activities and Conferences
- Dr Ahmed Kheiri won the top prize at the ROADEF/EURO challenge
- Special session on Combinatorial Optimisation and Heuristics at UKCI 2016.
- Workshop on Natural Computing in Scheduling and Timetabling at PPSN2016.
- Tutorial on Evolutionary Algorithms and Hyper-Heuristics, ECTA 2015.
- Tutorial on Hyper-Heuristics and Computational Intelligence, SSCI 2015.
- Tutorial on Hyper-heuristics, GECCO 2015, Madrid, Spain, July 11-15, 2015.
- 5th Workshop on Evolutionary Computation for the Automated Design of Algorithms (ECADA), July 11-15, 2015 @ GECCO 2015 in Madrid, Spain.
- Special Session on Evolutionary Computation in Hyper-heuristics at CEC'2015.
- Stream on Meta-heuristics at OR56.
- Workshop on Fundamentals of Hyper-heuristics at AI-2014, the thirty-fourth SGAI International Conference on Artificial Intelligence.
- Stream on Heuristic & Metaheuristics stream at APMOD 2014.
- Workshop on Scaling Behaviours of Landscapes, Parameters and Algorithms at PPSN 2014.
- Stream on Workshop on The Automated Design of Algorithms" at GECCO'2014
- Workshop on Metaheuristic Design Patterns at GECCO'2014
- Tutorial on Automatic Design of Algorithms via Hyper-heuristic Genetic Programming at PPSN'2014
- Special Session on Evolutionary Computation in Combinatorial Optimization at CEC2014
- Stream on Meta-heuristics at OR55.
- Tutorial on "Hyper-Heuristics for Combinatorial Optimization" at MICAI 2013
- Track on Self-* Search at GECCO 2013
- Special Session on Hyper-heuristics in Search and Optimization at CEC2013
- Special Session on Modern Hyperheuristics for Large Scale Optimization Problems at META2012
- Special Session on Evolutionary based Hyper-heuristics and Their Applications at CEC2012
- Joint Workshop on Automated Selection and Tuning of Algorithms at PPSN2012
- Special Session on Hybrid Evolutionary Algorithms, Hyper-heuristics and Memetic Computation CEC2012
- Tutorial on Hyper-heuristics and Cross-domain Optimization at GECCO2012
- Workshop on Self-tuning, self-configuring and self-generating search heuristics at PPSN2010
- Workshop on Understanding Heuristics: How do we get the best of both theory and empirical methods? at PPSN2010
- Special Session on Cross-domain Heuristic Search at LION2012
- Tutorial on Automated Heuristic Design at GECCO2011
- Special Session on Systems to Build Systems at MISTA2011
References
- Burke, E. K., M. Hyde, G. Kendall, G. Ochoa, E. Ozcan, and R. Qu (2010). Hyper-heuristics: A Survey of the State of the Art, to appear at Journal of Operational Research Society, 2012.
- Burke, E. K., M. Hyde, G. Kendall, G. Ochoa, E. Ozcan, and J. Woodward (2009). A Classification of Hyper-heuristics Approaches, Handbook of Metaheuristics, International Series in Operations Research & Management Science, In M. Gendreau and J-Y Potvin (Eds.), Springer (in press).
- Burke, E. K., Kendall, G., Newall, J., Hart, E., Ross P. and Schulenburg, S. (2003) Hyper-Heuristics: An Emerging Direction in Modern Search Technology, Chapter 16 in Handbook of Meta-Heuristics, (Eds. F. Glover and G. Kochenberger), Kluwer Academic Publishers, 457-474.
- Ross, P. (2005) Hyper-heuristics, Chapter 17 in Search Methodologies: Introductory Tutorials in Optimization and Decision Support Methodologies (Eds. E.K.Burke and G.Kendall), Springer, 529-556
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