An Improved Maximum Neural Network Algorithm for Maximum Cut Problem
نویسنده
چکیده
In this paper, we propose a new parallel algorithm that can help the maximum neural network escape from local minima for maximum cut problem. By adding a nonlinear self-feedback to the maximum neural network, the proposed parallel algorithm has richer and more flexible dynamics and can prevent the network from getting stuck at local minima. A large number of instances have been simulated to verify the proposed algorithm. Keywords— Maximum cut problem, maximum neural network, nonlinear self-feedback, NP-complete problem
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