Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Non-parametric Estimation of Properties of Combinatorial Landscapes
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
On confidence intervals for the number of local optima
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
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This paper introduces the design of superconductive magnet configurations in Magnetic Resonance Imaging (MRI) systems as a challenging real-world problem for Evolutionary Algorithms (EAs). Analysis of the problem structure is conducted using a general statistical method, which could be easily applied to other problems. The results suggest that the problem is highly multimodal and likely to present a significant challenge for many algorithms. Through a series of preliminary experiments, a continuous Estimation of Distribution Algorithm (EDA) is shown to be able to generate promising designs with a small computational effort. The importance of utilizing problem-specific knowledge and the ability of an algorithm to capture dependencies in solving complex real-world problems is also highlighted.