Abstract

The scheduling of production and logistic systems is challenging due to their structural complexity and the dynamic requirements which influence their operation. In this paper we propose and test a simulation-based procedure for defining optimal integrated schedules for production and logistic processes along a global supply chain involving a production job shop and intermodal transport. The procedure is based on a hybrid simulation-optimization approach, which combines linear programing, discrete event simulation and a numerical experiment. The combination provides the capability of dealing with complex optimization problems, while properly considering stochastic behaviors. The results obtained in a test case scenario evidenced the capability of the proposed approach.

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