An example of simulation optimisation using a neural network metamodel: finding the optimum number of kanbans in a manufacturing system |
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Authors: | R D Hurrion |
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Affiliation: | 1.University of Warwick,UK |
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Abstract: | A method of finding the optimum solution for a stochastic discrete-event system is described. A simulation model of the system is first built and then used to train a neural network metamodel. The optimisation process consists of using the metamodel to find an approximate optimum solution. This solution is then used by the simulation as the starting point in a more precise search for an optimum. The approach is demonstrated with an example that finds the optimum number of kanbans needed to control a manufacturing system. |
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