A noisy chaotic neural network for solving combinatorial optimization problems: Stochastic chaotic simulated annealing

作者：Wang, LP^*; Li, S; Tian, FY; Fu, XJ

来源：IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics , 2004, 34(5): 2119-2125.

DOI：10.1109/TSMCB.2004.829778

• channel assignment
• chaos
• combinatorial optimization
• neural network

Recently Chen and Aihara have demonstrated both experimentally and mathematically that their chaotic simulated annealing (CSA) has better search ability for solving combinatorial optimization problems compared to both the Hopfield-Tank approach and stochastic simulated annealing (SSA). However, CSA may not find a globally optimal solution no matter how slowly annealing is carried out, because the chaotic dynamics are completely deterministic. In contrast, SSA tends to settle down to a global optimum if the temperature is reduced sufficiently slowly. Here we combine the best features of both SSA and CSA, thereby proposing a new approach for solving optimization problems, i.e., stochastic chaotic simulated annealing, by using a noisy chaotic neural network. We show the effectiveness of this new approach with two difficult combinatorial optimization problems, i.e., a traveling salesman problem and a channel assignment problem for cellular mobile communications.

• 出版日期2004-10
• 单位湘潭大学; 中国人民解放军信息工程大学; 南阳理工学院