Aims, Scope and List of Topics
Designing metaheuristics to solve problems can be time consuming, requiring many man hours. This involves making a number of design decisions such as parameter tuning, identifying moves or operators to use, deciding on the control flow of the algorithm or determining which low-level heuristics to use in the case of combinatorial optimization problems. In some cases it may be necessary to create new operators or algorithms or hybridize different metaheuristics to solve a problem. Hyper-heuristics and adaptive metaheuristics have proven to be effective for making some of these design decisions, thereby facilitating automated design. Hyper-heuristics have been successfully used for the selection and generation of lowlevel heuristics in solving various combinatorial optimization problems including timetabling, vehicle routing and packing problems, amongst others and have also been applied to dynamic environments and multiobjective optimization. More recent trends in hyper-heuristic research have focused on the design of metaheuristics. Selection hyper-heuristics have been used for determining parameter values, choice of operators and control flow in metaheuristics, e.g. evolutionary algorithms and ant colonization, as well as for the hybridization of techniques, e.g. multiobjective evolutionary algorithms, different metaheuristics.Generation hyper-heuristics have been employed to create new operators for metaheuristics, e.g. selection and mutation operators. An emerging area in hyper-heuristics is hyper-hyper-heuristics, i.e. using hyper-heuristics to generate or design hyper-heuristics. The aim of this special session is for researchers to present recent developments in the field thereby paving the way for future advancement.
The main topics include but are not limited to:
- Applications of selection and generative hyper-heuristics
- Hyper-heuristics for metaheuristic design, e.g. parameter tuning, control flow, operator selection
- Hyper-heuristics for the creation of new operators and algorithms
- Hyper-heuristics for the derivation of hybrid methods, e.g. hybridization of metaheuristics
- Hyper-heuristics for the design hyper-heuristics
- Cross domain applications of hyper-heuristics
- Parallelization of hyper-heuristics
- Theoretical aspects of hyper-heuristics
Organizers
Nelishia Pillay,University of KwaZulu-Natal, South Africa
E-mail: pillayn32@ukzn.ac.za
Rong Qu,
University of Nottingham, UK
E-mail: Rong.Qu@nottingham.ac.uk
Hisao Ishibuchi,
Osaka Prefecture University, Japan
E-mail: hisaoi@cs.osakafu-u.ac.jp
Important Dates
Paper submission deadline: 15 January, 2016Paper acceptance notification: 15 March, 2016
Final paper submission deadline: 15 April, 2016
Early registration: 15 April, 2016
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