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A stochastic hyper-heuristic for optimising through comparisons

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1 Author(s)
Greer, K. ; Distrib. Comput. Syst., Belfast, UK

This paper introduces a new hyper-heuristic framework for automatically searching and changing potential solutions to a particular problem. The solutions and the problem datasets are placed into a grid and then a game is played to try and optimise the total cost over the whole grid, using a randomising process. The randomisation could be compared to a simulated annealing approach, where the aim is to improve the solution space as a whole, possibly at the expense of certain better solutions. It is hoped that this will give the solution search an appropriate level of robustness to allow it to avoid local optima.

Published in:

Knowledge Acquisition and Modeling (KAM), 2010 3rd International Symposium on

Date of Conference:

20-21 Oct. 2010