A combined model predictive control and time series forecasting framework for production-inventory systems

Doganis, P; Aggelogiannaki, E; Sarimveis, H

dc.contributor.author	Doganis, P	en
dc.contributor.author	Aggelogiannaki, E	en
dc.contributor.author	Sarimveis, H	en
dc.date.accessioned	2014-03-01T01:27:39Z
dc.date.available	2014-03-01T01:27:39Z
dc.date.issued	2008	en
dc.identifier.issn	0020-7543	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18522
dc.subject	Forecasting	en
dc.subject	Genetic algorithms	en
dc.subject	Inventory control	en
dc.subject	Model predictive control	en
dc.subject	Neural networks	en
dc.subject	Process control	en
dc.subject	Production planning	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.classification	Engineering, Manufacturing	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Competition	en
dc.subject.other	Control theory	en
dc.subject.other	Forecasting	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Genetic engineering	en
dc.subject.other	Inventory control	en
dc.subject.other	Neural networks	en
dc.subject.other	Planning	en
dc.subject.other	Predictive control systems	en
dc.subject.other	Process engineering	en
dc.subject.other	Production control	en
dc.subject.other	Supply chains	en
dc.subject.other	Time series analysis	en
dc.subject.other	Vegetation	en
dc.subject.other	Accurate predictions	en
dc.subject.other	Control actions	en
dc.subject.other	Control performances	en
dc.subject.other	Forecast accuracies	en
dc.subject.other	Forecasting models	en
dc.subject.other	Inventory systems	en
dc.subject.other	Management frameworks	en
dc.subject.other	Optimization problems	en
dc.subject.other	Production planning	en
dc.subject.other	Real times	en
dc.subject.other	Time series	en
dc.subject.other	Model predictive control	en
dc.title	A combined model predictive control and time series forecasting framework for production-inventory systems	en
heal.type	journalArticle	en
heal.identifier.primary	10.1080/00207540701523058	en
heal.identifier.secondary	http://dx.doi.org/10.1080/00207540701523058	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Model Predictive Control (MPC) has been previously applied to supply chain problems with promising results; however most systems that have been proposed so far possess no information on future demand. The incorporation of a forecasting methodology in an MPC framework can promote the efficiency of control actions by providing insight in the future. In this paper this possibility is explored, by proposing a complete management framework for production-inventory systems that is based on MPC and on a neural network time series forecasting model. The proposed framework is tested on industrial data in order to assess the efficiency of the method and the impact of forecast accuracy on the overall control performance. To this end, the proposed method is compared with several alternative forecasting approaches that are implemented on the same industrial dataset. The results show that the proposed scheme can improve significantly the performance of the production-inventory system, due to the fact that more accurate predictions are provided to the formulation of the MPC optimization problem that is solved in real time.	en
heal.publisher	TAYLOR & FRANCIS LTD	en
heal.journalName	International Journal of Production Research	en
dc.identifier.doi	10.1080/00207540701523058	en
dc.identifier.isi	ISI:000260572700003	en
dc.identifier.volume	46	en
dc.identifier.issue	24	en
dc.identifier.spage	6841	en
dc.identifier.epage	6853	en