Abstract
In this article we present a modified transiently chaotic neural network model and then use it to solve the 0/1 knapsack problem. During the chaotic searching the gain of the neurons is gradually sharpened, this strategy can accelerate the convergence of the network to a binary state and keep the satisfaction of the constraints. The simulation demonstrates that the approach is efficient both in approximating the global solution and the number of iterations.
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Wang, B., Dong, H. & He, Z. A Chaotic Annealing Neural Network with Gain Sharpening and Its Application to the 0/1 Knapsack Problem. Neural Processing Letters 9, 243–247 (1999). https://doi.org/10.1023/A:1018603904290
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DOI: https://doi.org/10.1023/A:1018603904290