Integrated Supply Chain Optimization Model Using Mixed Integer Linear Programming
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This article presents an integrated approach to optimize the different functions in a supply chain on strategic tactical and operational levels. The integrated supply chain model has been formulated as a cost minimization problem in the form of MILP (Mixed Integer Linear Programming). The costs of production, transport, distribution and environmental protection were adopted as optimization criteria. Timing, volume, capacity and mode of transport were also taken into account. The model was implemented in the LINGO package. The implementation model and the numerical tests are presented and discussed. The numerical experiments were carried out using sample data to show the possibilities of practical decision support and optimization of the supply chain.
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