<?xml version="1.0" encoding="UTF-8"?> <article key="pdf/6113" mdate="2008-03-25 00:00:00"> <author>Philip Doganis and Eleni Aggelogiannaki and Haralambos Sarimveis</author> <title>A Model Predictive Control and Time Series Forecasting Framework for Supply Chain Management</title> <pages>315 - 319</pages> <year>2008</year> <volume>2</volume> <number>3</number> <journal>International Journal of Industrial and Manufacturing Engineering</journal> <ee>https://publications.waset.org/pdf/6113</ee> <url>https://publications.waset.org/vol/15</url> <publisher>World Academy of Science, Engineering and Technology</publisher> <abstract>Model Predictive Control has been previously applied to supply chain problems with promising results; however hitherto proposed systems possessed no information on future demand. A forecasting methodology will surely promote the efficiency of control actions by providing insight on the future. A complete supply chain management framework that is based on Model Predictive Control (MPC) and Time Series Forecasting will be presented in this paper. The proposed framework will be tested on industrial data in order to assess the efficiency of the method and the impact of forecast accuracy on overall control performance of the supply chain. To this end, forecasting methodologies with different characteristics will be implemented on test data to generate forecasts that will serve as input to the Model Predictive Control module.</abstract> <index>Open Science Index 15, 2008</index> </article>