In a wireless multi-hop network, some nodes relay packets in order to transfer messages. Scheduling problems in such a network is ones that nodes associate packets with as few frequency-bands / time-slots as possible. In this report we deal with a broadcast scheduling problem. This problem is known to be NP-hard, and so we cannot find an optimal solution in polynomial time. A hopfield neural network does not usually find an optimal solution of an NP-hard problem. To avoid converging on a local minimum, chaotic approach has been studied recently. In this report we apply a chaotic hopfield neural network to the broadcast scheduling problem, and we show that this approach has better performance than a previous algorithm.
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