Dynamic modeling and control of supply chain systems: A review

Sarimveis, H; Patrinos, P; Tarantilis, CD; Kiranoudis, CT

dc.contributor.author	Sarimveis, H	en
dc.contributor.author	Patrinos, P	en
dc.contributor.author	Tarantilis, CD	en
dc.contributor.author	Kiranoudis, CT	en
dc.date.accessioned	2014-03-01T01:28:11Z
dc.date.available	2014-03-01T01:28:11Z
dc.date.issued	2008	en
dc.identifier.issn	0305-0548	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18748
dc.subject	Control	en
dc.subject	Dynamic modeling	en
dc.subject	Dynamic programming	en
dc.subject	Model predictive control	en
dc.subject	Review	en
dc.subject	Supply chain management	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Engineering, Industrial	en
dc.subject.classification	Operations Research & Management Science	en
dc.subject.other	Competition	en
dc.subject.other	Dynamic models	en
dc.subject.other	Dynamic programming	en
dc.subject.other	Dynamical systems	en
dc.subject.other	Freight transportation	en
dc.subject.other	Model predictive control	en
dc.subject.other	Neurodynamic programming	en
dc.subject.other	Supply chain managers	en
dc.subject.other	Supply chain management	en
dc.title	Dynamic modeling and control of supply chain systems: A review	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/j.cor.2007.01.017	en
heal.identifier.secondary	http://dx.doi.org/10.1016/j.cor.2007.01.017	en
heal.language	English	en
heal.publicationDate	2008	en
heal.abstract	Supply chains are complicated dynamical systems triggered by customer demands. Proper selection of equipment, machinery, buildings and transportation fleets is a key component for the success of such systems. However, efficiency of supply chains mostly depends on management decisions, which are often based on intuition and experience. Due to the increasing complexity of supply chain systems (which is the result of changes in customer preferences, the globalization of the economy and the stringy competition among companies), these decisions are often far from optimum. Another factor that causes difficulties in decision making is that different stages in supply chains are often supervised by different groups of people with different managing philosophies. From the early 1950s it became evident that a rigorous framework for analyzing the dynamics of supply chains and taking proper decisions could improve substantially the performance of the systems. Due to the resemblance of supply chains to engineering dynamical systems, control theory has provided a solid background for building such a framework. During the last half century many mathematical tools emerging from the control literature have been applied to the supply chain management problem. These tools vary from classical transfer function analysis to highly sophisticated control methodologies, such as model predictive control (MPC) and neuro-dynamic programming. The aim of this paper is to provide a review of this effort. The reader will find representative references of many alternative control philosophies and identify the advantages, weaknesses and complexities of each one. The bottom line of this review is that a joint co-operation between control experts and supply chain managers has the potential to introduce more realism to the dynamical models and develop improved supply chain management policies. (c) 2007 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	Computers and Operations Research	en
dc.identifier.doi	10.1016/j.cor.2007.01.017	en
dc.identifier.isi	ISI:000255671800010	en
dc.identifier.volume	35	en
dc.identifier.issue	11	en
dc.identifier.spage	3530	en
dc.identifier.epage	3561	en