Journal
COMPUTERS & OPERATIONS RESEARCH
Volume 36, Issue 6, Pages 1935-1944Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2008.06.010
Keywords
Container terminal; Genetic algorithm; Hybrid flow shop problem; Simulation optimization
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In this paper, a simulation optimization method for scheduling loading operations in container terminals is developed. The method integrates the intelligent decision mechanism of optimization algorithm and evaluation function of simulation model, its procedures are: initializing container sequence according to certain dispatching rule, then improving the sequence through genetic algorithm, using simulation model to evaluate objective function of a given scheduling scheme. Meanwhile, a surrogate model based on neural network is designed to predict objective function and filter out potentially bad solutions thus, to decrease the times of running simulation model. Numerical tests show that simulation optimization method can solve the scheduling problem of container terminals efficiently. And the surrogate model can improve the computation efficiency of simulation optimization. Crown Copyright (C) 2008 Published by Elsevier Ltd. All rights reserved.
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