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Genetic Algorithms for Multiple-Choice Problems
This thesis investigates the use of problem-specific knowledge to enhanc...
04/19/2010 ∙ by Uwe Aickelin, et al. ∙
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Resolving the Complexity of Some Fundamental Problems in Computational Social Choice
This thesis is in the area called computational social choice which is a...
03/23/2017 ∙ by Palash Dey, et al. ∙
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Evolutionary Optimisation Methods for Template Based Image Registration
This paper investigates the use of evolutionary optimisation techniques ...
05/11/2007 ∙ by Lukasz A Machowski, et al. ∙
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Efficient Noisy Optimisation with the Sliding Window Compact Genetic Algorithm
The compact genetic algorithm is an Estimation of Distribution Algorithm...
08/07/2017 ∙ by Simon M. Lucas, et al. ∙
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Optimizing genetic algorithm strategies for evolving networks
This paper explores the use of genetic algorithms for the design of netw...
04/07/2004 ∙ by Matthew J. Berryman, et al. ∙
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Applying Partial-ACO to Large-scale Vehicle Fleet Optimisation
Optimisation of fleets of commercial vehicles with regards scheduling ta...
04/16/2019 ∙ by Darren M. Chitty, et al. ∙
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A Denoising Autoencoder that Guides Stochastic Search
An algorithm is described that adaptively learns a non-linear mutation d...
04/06/2014 ∙ by Alexander W. Churchill, et al. ∙
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Dienstplanerstellung in Krankenhaeusern mittels genetischer Algorithmen
05/30/2013 ∙ by Uwe Aickelin, et al. ∙
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This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems. It shows that such information can significantly enhance performance, but that the choice of information and the way it is included are important factors for success.
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