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Geometry of evolutionary algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation, 2011The various flavors of Evolutionary Algorithms look very similar when cleared of algorithmically irrelevant differences such as domain of application and phenotype interpretation. Representation-independent algorithmic characteristics like the selection scheme can be freely exchanged between algorithms.
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An Evolutionary Clustering Algorithm
2004There are many heuristic algorithms for clustering, from which the most important are the hierarchical methods of agglomeration, especially the Ward’s method. Among the iterative methods the most universally used is the C–means method and it’s generalizations.
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Evolutionary Algorithms and Their Applications to Engineering Problems
Neural Computing and Applications, 2020Halina Kwaśnicka, Adam Slowik
exaly
Many-Objective Evolutionary Algorithms
ACM Computing Surveys, 2015Xin Yao, Ke Tang, Jinlong Li
exaly
A Systematic Literature Review of Adaptive Parameter Control Methods for Evolutionary Algorithms
ACM Computing Surveys, 2017Irène Moser, Aldeida Aleti
exaly
Parameter Control in Evolutionary Algorithms
IEEE Transactions on Evolutionary Computation, 1999Zbigniew Michalewicz, A E Eiben
exaly
MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition
IEEE Transactions on Evolutionary Computation, 2007Hui Li, Qingfu Zhang
exaly