NDLI: Variable solution structure can be helpful in evolutionary optimization

Content Provider	Springer Nature Link
Author	Qian, Chao Yu, Yang Zhou, Zhi Hua
Copyright Year	2015
Abstract	Evolutionary algorithms are a family of powerful heuristic optimization algorithms where various representations have been used for solutions. Previous empirical studies have shown that for achieving a better efficiency of evolutionary optimization, it is often helpful to adopt rich representations (e.g., trees and graphs) rather than ordinary representations (e.g., binary coding). Such a recognition, however, has little theoretical justifications. In this paper, we present a running time analysis on genetic programming. In contrast to previous theoretical efforts focused on simple synthetic problems, we study two classical combinatorial problems, the maximum matching and the minimum spanning tree problems. Our theoretical analysis shows that evolving tree-structured solutions is much more efficient than evolving binary vector encoded solutions, which is also verified by experiments. The analysis discloses that variable solution structure might be helpful in evolutionary optimization when the solution complexity can be well controlled. 1. 对于采用可变结构来表示组合优化的解, 以往认为由于表达更加自然从而可帮助演化算法更好的进行优化, 当仅有实验支持、尚缺乏理论支撑, 本文对使用树形解结构的遗传规划算法进行时间复杂度分析, 在最大匹配和最小生成树问题上的分析结果显示了这种可变解结构的有效性, 为可变解结构的使用提供了理论证据。 2. 对于遗传规划算法的时间复杂度分析, 以往主要在人造简单问题上开展, 本文首次给出在组合优化问题上的分析结果, 增进了对遗传规划算法的理论理解。
Starting Page	1
Ending Page	17
Page Count	17
File Format	PDF
ISSN	1674733X
Journal	Science in China Series : Information Sciences
Volume Number	58
Issue Number	11
e-ISSN	18691919
Language	Chinese
Publisher	Science China Press
Publisher Date	2015-09-21
Publisher Place	Beijing
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	演化算法遗传规划最大匹配最小生成树运行时间计算复杂度 Information Systems and Communication Service
Content Type	Text
Resource Type	Article
Subject	Computer Science

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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