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Titlebook: Evolutionary Computation in Combinatorial Optimization; 15th European Confer Gabriela Ochoa,Francisco Chicano Conference proceedings 2015 S

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樓主: Randomized
41#
發(fā)表于 2025-3-28 15:07:06 | 只看該作者
42#
發(fā)表于 2025-3-28 19:32:43 | 只看該作者
Positive Semidefinite Matrices,very specific population of individuals. Indeed, the main characteristic of . is to work with a population of only two individuals. This provides a very simple algorithm with neither selection operator nor replacement strategy. Because of its simplicity, . allows an easy way for managing the diversi
43#
發(fā)表于 2025-3-28 23:16:50 | 只看該作者
Similarity on a Euclidean Plane (SIM),f epidemics. Recently, this problem gained interest from the softcomputing research community and papers were published on applications of ant colony optimization and evolutionary algorithms to this problem. Also, the multiobjective version of the problem was formulated..In this paper a multipopulat
44#
發(fā)表于 2025-3-29 03:36:26 | 只看該作者
Schwinger-DeWitt Asymptotic Expansioncific solver that provably computes the true Pareto Front of the resulting instances. A wide range of Pareto Front shapes of various difficulty can be obtained by varying the parameters of the generator. The experimental performances of an actual implementation of the exact solver are demonstrated,
45#
發(fā)表于 2025-3-29 07:50:14 | 只看該作者
46#
發(fā)表于 2025-3-29 11:56:24 | 只看該作者
47#
發(fā)表于 2025-3-29 15:40:17 | 只看該作者
48#
發(fā)表于 2025-3-29 23:25:40 | 只看該作者
Glue-Laminated Timber from, spp.,Mixing Network Extremal Optimization is a new algorithm designed to identify the community structure in networks by using a game theoretic approach and a network mixing mechanism as a diversity preserving method. Numerical experiments performed on synthetic and real networks illustrate the potential of the approach.
49#
發(fā)表于 2025-3-30 00:58:26 | 只看該作者
Mixing Network Extremal Optimization for Community Structure Detection,Mixing Network Extremal Optimization is a new algorithm designed to identify the community structure in networks by using a game theoretic approach and a network mixing mechanism as a diversity preserving method. Numerical experiments performed on synthetic and real networks illustrate the potential of the approach.
50#
發(fā)表于 2025-3-30 04:13:51 | 只看該作者
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