Dynamic model of multi-agent social evolutionary 
algorithm and its convergence

doi:10.1016/S1005-8885(13)60118-1

中国邮电高校学报(英文) ›› 2013, Vol. 20 ›› Issue (6): 122-128.doi: 10.1016/S1005-8885(13)60118-1

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Dynamic model of multi-agent social evolutionary algorithm and its convergence

潘晓英,陈皓

School of Computer Science & Technology, Xi’an University of Posts & Telecommunications, Xi’an 710121, China

收稿日期:2013-06-05 修回日期:2013-10-20 出版日期:2013-12-31 发布日期:2013-12-27
通讯作者: 潘晓英 E-mail:panxiaoying@xupt.edu.cn
基金资助:
This work was supported by the National Natural Science Foundation of China (61105064, 61203311, 61373116), the Natural Science Basic Research Plan in Shaanxi Province of China (2011JM8007), the Ministry of Education Key Laboratory (IPIU012011007).

Dynamic model of multi-agent social evolutionary algorithm and its convergence

School of Computer Science & Technology, Xi’an University of Posts & Telecommunications, Xi’an 710121, China

Received:2013-06-05 Revised:2013-10-20 Online:2013-12-31 Published:2013-12-27
Contact: Xiao-Ying PAN E-mail:panxiaoying@xupt.edu.cn
Supported by:
This work was supported by the National Natural Science Foundation of China (61105064, 61203311, 61373116), the Natural Science Basic Research Plan in Shaanxi Province of China (2011JM8007), the Ministry of Education Key Laboratory (IPIU012011007).

摘要/Abstract

摘要： With a typical and simple 2-bit problem, a dynamic model of multi-agent social evolutionary algorithm (MASEA) is constructed by dynamic method. Then, the global dynamic shape of MASEA is comprehensively analyzed and the common evolution operators are also formally described. Furthermore, the effect that every evolutionary operator has on the dynamic shape is discovered by attraction analysis of the fixed points in the models. The global convergence of MASEA is also proved.

关键词: multi-agent social evolutionary algorithm, fixed point, attractive point, attractiveness

Abstract: With a typical and simple 2-bit problem, a dynamic model of multi-agent social evolutionary algorithm (MASEA) is constructed by dynamic method. Then, the global dynamic shape of MASEA is comprehensively analyzed and the common evolution operators are also formally described. Furthermore, the effect that every evolutionary operator has on the dynamic shape is discovered by attraction analysis of the fixed points in the models. The global convergence of MASEA is also proved.

Key words: multi-agent social evolutionary algorithm, fixed point, attractive point, attractiveness

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Dynamic model of multi-agent social evolutionary algorithm and its convergence

Dynamic model of multi-agent social evolutionary algorithm and its convergence

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