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- W129167759 abstract "Abstract This paper proposes a model of an application of Hopfield neural network to the Flexible Manufacturing Systems scheduling problem. The cyclic scheduling of this problem is NP-hard. This model describes details in calculating Work In Progress from the schedule taking into account the corresponding linked, precedence and disjunctive constraints. An unconstrained optimisation model is formulated and a methodology of applying Hopfield neural network is given. Three different scheduling benchmarks are used for testing and comparative experimental results are provided, with a conclusion discussed indicating the advantage of this approach." @default.
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- W129167759 date "2006-01-01" @default.
- W129167759 modified "2023-10-14" @default.
- W129167759 title "APPLICATION OF IMPROVED HOPFIELD NETWORK TO CYCLIC FMS SCHEDULING" @default.
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- W129167759 doi "https://doi.org/10.3182/20060517-3-fr-2903.00054" @default.
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