title: A flexible annealing chaotic neural network to maximum clique problem.
abstract: Based on the analysis and comparison of several annealing strategies, we present a flexible annealing chaotic neural network which has flexible controlling ability and quick convergence rate to optimization problem. The proposed network has rich and adjustable chaotic dynamics at the beginning, and then can converge quickly to stable states. We test the network on the maximum clique problem by some graphs of the DIMACS clique instances, p-random and k random graphs. The simulations show that the flexible annealing chaotic neural network can get satisfactory solutions at very little time and few steps. The comparison between our proposed network and other chaotic neural networks denotes that the proposed network has superior executive efficiency and better ability to get optimal or near-optimal solution.
authors.affiliation: Faculty of Engineering, University of Toyama, Toyama-shi, 930-8555, Japan. yanggang1979@hotmail.com
authors.forename: Gang
authors.initials: G
authors.lastname: Yang
authors.forename: Zheng
authors.initials: Z
authors.lastname: Tang
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Zhang
authors.forename: Yunyi
authors.initials: Y
authors.lastname: Zhu
mesh_terms: D001185:Artificial Intelligence; D003198:Computer Simulation; D008433:Mathematics; D008959:Models, Neurological; D016571:Neural Networks, Computer