找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Evolutionary Learning: Advances in Theories and Algorithms; Zhi-Hua Zhou,Yang Yu,Chao Qian Book 2019 Springer Nature Singapore Pte Ltd. 20

[复制链接]
楼主: ARGOT
发表于 2025-3-28 18:19:06 | 显示全部楼层
PreliminariesThis chapter introduces preliminaries. Including basic evolutionary algorithms, pseudo-Boolean functions for theoretical studies, and basic knowledge for analyzing running time complexity of evolutionary algorithms.
发表于 2025-3-28 22:10:28 | 显示全部楼层
RecombinationThis chapter studies the influence of recombination operators. We show that, in multi-objective evolutionary optimization, recombination operators are useful for multi-objective evolutionary optimization by accelerating the filling of the Pareto front. This principle may also hold in more situations.
发表于 2025-3-28 22:56:49 | 显示全部楼层
发表于 2025-3-29 03:51:06 | 显示全部楼层
PopulationThis chapter studies the influence of population on evolutionary algorithms. We show that, on one hand, population is unexpected for simple functions such as OneMax and LeadningOnes by derving the lower running time bound, and on the other hand, in the presence of noise, using population can enhance the robustness against noise.
发表于 2025-3-29 07:45:37 | 显示全部楼层
发表于 2025-3-29 11:40:50 | 显示全部楼层
发表于 2025-3-29 17:01:52 | 显示全部楼层
发表于 2025-3-29 22:51:30 | 显示全部楼层
发表于 2025-3-30 03:23:00 | 显示全部楼层
s for the analysis of running time and approximation performance in evolutionary algorithms. Based on these general tools, Part III presents a number of theoretical findings on major factors in evolutionary opt978-981-13-5956-9
发表于 2025-3-30 05:21:17 | 显示全部楼层
Running Time Analysis: Convergence-based Analysisrom bridging two fundamental theoretical issues. The approach is applied to show the exponential lower bound of the expected running time for (1+1)-EA and randomized local search solving the constrained Trap problem.
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-6-10 02:53
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表