文献类型：期刊文献

英文题名：Parallel optimization based on generalized cellular automata

作者：Shuai, Dianxun[1]; Xu, Li D.[2]; Zhang, Bin[1]

机构：[1] Department of Computer Science and Engineering, East China University of Science and Technology, 200237 Shanghai, China; [2] College of Business and Public Administration, Old Dominion University, Norfolk, VA 23529-0218, United States

年份：2006

卷号：5

起止页码：3804

外文期刊名：Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

收录：EI(收录号：20073510787060)

语种：英文

外文关键词：Computation theory - Matrix algebra - Optimization - Parallel processing systems

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, ? 2006 IEEE.