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The Application of the Combinatorial Optimization Problems Based on Preventive Feedback Pulse Coupled Neural Network

Pulse Coupled Neural Network (PCNN) with the phenomena of synchronous pulse bursts is different from traditional artificial neural networks. In this paper, the auto-wave in PCNN is used to solve combination optimization problems. The preventive feedback based on triangle inequality theorem is introduced to prevent bad solutions, and Preventive Feedback Pulse Coupled Neural Network (PFPCNN) is presented. In the process of searching solutions, the solution space complexity of combinatorial optimization problems is reduced and the efficiency and accuracy is improved. This algorithm is applied to SP, TSP simulation. The results show that the algorithm can effectively reduce space complexity and improve the searching speed further.The method based on auto-wave to solve combination optimization problems is a more quickly, more stable.