Preface: Special issue on "Understanding of Evolutionary Optimization Behavior", Part 2.
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- Natural Computing, 2022, v. 21, n. 2, p. 127, doi. 10.1007/s11047-021-09859-x
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Works matching IS 15677818 AND DT 2022 AND VI 21 AND IP 2
Results: 12
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On sampling error in genetic programming.
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- Natural Computing, 2022, v. 21, n. 2, p. 173, doi. 10.1007/s11047-020-09828-w
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3
Analyzing randomness effects on the reliability of exploratory landscape analysis.
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- Natural Computing, 2022, v. 21, n. 2, p. 131, doi. 10.1007/s11047-021-09847-1
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- Article
4
A new taxonomy of global optimization algorithms.
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- Natural Computing, 2022, v. 21, n. 2, p. 219, doi. 10.1007/s11047-020-09820-4
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5
Visualizations for rule-based machine learning.
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- Natural Computing, 2022, v. 21, n. 2, p. 243, doi. 10.1007/s11047-020-09840-0
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- Article
6
Similarity in metaheuristics: a gentle step towards a comparison methodology.
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- Natural Computing, 2022, v. 21, n. 2, p. 265, doi. 10.1007/s11047-020-09837-9
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7
Understanding measure-driven algorithms solving irreversibly ill-conditioned problems.
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- Natural Computing, 2022, v. 21, n. 2, p. 289, doi. 10.1007/s11047-020-09836-w
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8
The influence of fitness landscape characteristics on particle swarm optimisers.
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- Natural Computing, 2022, v. 21, n. 2, p. 335, doi. 10.1007/s11047-020-09835-x
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9
The fractal geometry of fitness landscapes at the local optima level.
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- Natural Computing, 2022, v. 21, n. 2, p. 317, doi. 10.1007/s11047-020-09834-y
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10
Classifying Metaheuristics: Towards a unified multi-level classification system.
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- Natural Computing, 2022, v. 21, n. 2, p. 155, doi. 10.1007/s11047-020-09824-0
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11
Gamesourcing: an unconventional tool to assist the solution of the traveling salesman problem.
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- Natural Computing, 2022, v. 21, n. 2, p. 347, doi. 10.1007/s11047-020-09817-z
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12
Comparison of synchronous and asynchronous parallelization of extreme surrogate-assisted multi-objective evolutionary algorithm.
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- Natural Computing, 2022, v. 21, n. 2, p. 187, doi. 10.1007/s11047-020-09806-2
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- Article