A greedy hyper-heuristic in dynamic environments

Ender Ozcan, Sima Etaner Uyar, Edmund Burke
2009 Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09  
If an optimisation algorithm performs a search in an environment that changes over time, it should be able to follow these changes and adapt itself for handling them in order to achieve good results. Different types of dynamics in a changing environment require the use of different approaches. Hyper-heuristics represent a class of methodologies that are high level heuristics performing search over a set of low level heuristics. Due to the generality of hyperheuristic frameworks, they are
more » ... d to be adaptive. Hence, a hyper-heuristic can be used in a dynamic environment to determine the approach to apply, adapting itself accordingly at each change. This study presents an initial investigation of hyper-heuristics in dynamic environments. A greedy hyper-heuristic is tested over a set of benchmark functions.
doi:10.1145/1570256.1570302 dblp:conf/gecco/OzcanUB09 fatcat:6jg6inlx4vcfblfkukoknefu4e