Parallel optimization based on generalized cellular automata

被引：0

作者：

Dianxun Shuai ^{[1
]}

Li D. Xu ^{[2
]}

Bin Zhang ^{[1
]}

机构：

[1] E China Univ Sci & Technol, Dept Comp Sci & Engn, Shanghai 200237, Peoples R China

[2] Old Dominion Univ, Coll Business & Publ Adm, Norfolk, VA 23529 USA

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS | 2006年

关键词：

D O I：

10.1109/ICSMC.2006.384723

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

the fast packet switching (FPS) in computer networks. This paper further extends GCA to effectively solving a class of optimization problems subject to a binary constraint matrix, including the FPS problem and the traveling salesman problem (TSP) that is NP-hard. In contrast to Hopfield-type neural networks and cellular neural networks, the proposed GCA approach has the pyramid architecture and evolutionary dynamics related to multi-granularity macro-cells. This paper discusses the details regarding the dynamics and properties of the improved GCA.erms of the solution quality.

引用

页码：3804 / +

页数：2

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