Modeling the genetic algorithm by a nonhomogeneous markov chain: Weak and strong ergodicity

Campos V.S.M.; Pereira A.G.C.; ROJAS CRUZ J.A.

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Modeling the genetic algorithm by a nonhomogeneous markov chain: Weak and strong ergodicity

机译：通过非均质马尔可夫链对遗传算法建模：弱而强的遍历性

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Evolutionary algorithms are used to search for optimal points of functions. One of these algorithms, the canonical genetic algorithm, uses in its dynamics two parameters, namely mutation and crossover probabilities, which are kept fixed throughout the algorithm's evolution. In this paper, changes in those parameters will be allowed and the convergence of this new algorithm will be analyzed. We also present an approach to weak ergodicity of a nonhomogeneous Markov chains without using directly Dobrushin's δ coefficient.

机译：进化算法用于搜索功能的最佳点。这些算法之一是规范遗传算法，它在动力学中使用两个参数，即变异和交叉概率，在整个算法发展过程中保持不变。在本文中，将允许更改这些参数，并将分析此新算法的收敛性。我们还提出了一种在不直接使用Dobrushinδ系数的情况下，对非均匀Markov链的弱遍历性进行处理的方法。

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《Theory of probability and its applications》 |2013年第1期|共8页
作者
Campos V.S.M.; Pereira A.G.C.; ROJAS CRUZ J.A.;
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正文语种 eng
中图分类概率论与数理统计;
关键词
Genetic algorithms; Markov chains; Nonhomogeneous; Weak and strong ergodicity;

机译：遗传算法;马尔可夫链;不均匀;弱强遍历性;

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1. Modeling the genetic algorithm by a nonhomogeneous markov chain: Weak and strong ergodicity [J] . Campos V.S.M., Pereira A.G.C., ROJAS CRUZ J.A. Theory of probability and its applications . 2013,第1期

机译：通过非均质马尔可夫链对遗传算法建模：弱而强的遍历性
2. The Strong Law of Large Numbers and the Entropy Ergodic Theorem for Nonhomogeneous Bifurcating Markov Chains Indexed by a Binary Tree [J] . Dang Hui, Yang Weiguo, Shi Zhiyan Information Theory, IEEE Transactions on . 2015,第4期

机译：二叉树索引的非齐叉分叉马尔可夫链的大数强定律和熵遍历定理
3. THE GENERALIZED ENTROPY ERGODIC THEOREM FOR NONHOMOGENEOUS MARKOV CHAINS INDEXED BY A HOMOGENEOUS TREE [J] . Probability in the Engineering and Informational Sciences . 2020,第2期

机译：均质树表示的非均质马尔可夫链的广义熵定理
4. On the Weak Ergodicity of the Markov Chain Associated with a Chaotic Simulated Annealing algorithm [C] . Guo Chen, Zhao Yang Dong IEEE Congress on Evolutionary Computation . 2008

机译：关于与混沌模拟退火算法相关的马尔可夫链的弱遍历
5. CHARACTERIZATIONS OF STRONG ERGODICITY FOR CONTINUOUS TIME MARKOV CHAINS. [D] . SCOTT, MARK. 1979

机译：连续时间马尔可夫链的强电性特征。
6. Multiscale Stochastic Reaction–Diffusion Algorithms Combining Markov Chain Models with Stochastic Partial Differential Equations [O] . Hye-Won Kang, Radek Erban -1

机译：马尔可夫链模型与随机偏微分方程相结合的多尺度随机反应扩散算法
7. Modeling the genetic algorithm by a nonhomogeneous Markov chain: weak and strong ergodicity [O] . V S. M. Campos, A G. C. Pereira, J A Rojas Cruz 2012

机译：用非均匀性马尔可夫链建模遗传算法：弱强的遍历

Modeling the genetic algorithm by a nonhomogeneous markov chain: Weak and strong ergodicity

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