Abstract
In this chapter, the basics of the SC multi-disciplinary treatment in the DIMA (Decentralized Integrated Modelling Approach) methodology are presented. The main principles of the DIMA are SC elements’ activity, multiple modelling, integration and decentralization. We consider these principles in detail in the course of the chapter. We introduce the concept of an “active modelling object” (AMO) as part of the generic model constructions. Integration is considered from four perspectives: the integration of various modelling approaches and frameworks, the integration of planning and execution models, the integration of decision-making levels, and the implementation of integration throughout “conceptual model → mathematical model → computation”. The integration and combined application of various models is implemented by means of multi-model complexes and qualimetry of models.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Barbasi AL (2005) Network theory - the emergence of the creative enterprise. Science 308:639–641
Beamon BM (1998) Supply chain design and analysis: models and methods. Int J of Prod Econ 55(3):281–294
Casti JL (1979) Connectivity, complexity and catastrophe in large-scale systems. Wiley-Interscience, New York and London
Harrison TP (2005) Principles for the strategic design of supply chains. In: Harrison TP, Lee H L, Neale JJ (Ed) The practice of supply chain management. Kluwer academic publishers, Boston
Ivanov D (2006) DIMA – Decentralized Integrated Modeling Approach. Ein Ansatz zur interdisziplinären Modellierung von Produktions- und Logistiknetzwerken. Verlag der GUC, Chemnitz
Ivanov D (2009a) DIMA – a research methodology for comprehensive multi-disciplinary modelling of production and logistics networks. Int J Prod Res 47(5):1133–1155
Ivanov D (2009b) An adaptive framework for aligning (re)planning decisions on supply chain strategy, design, tactics, and operations. Int J Prod Res, DOI: 10.1080/00207540902893417, in press
Ivanov D, Kaeschel J (2003) Vernetzte Planung und kontinuierliche Lieferkettenoptimierung. PPS-Management 4:29–32
Ivanov D, Arkhipov A, Sokolov B (2004) Intelligent Supply Chain Planning in Virtual Enterprises. In: Camarihna-Matos LM (Ed) Virtual Enterprises and Collaborative Networks. Kluwer academic publishers, Boston
Ivanov D, Kaeschel J, Arkhipov A, Sokolov B and Zschorn L (2005) Quantitative models of collaborative networks. In: Camarihna-Matos LM, Afsarmanesh H, Ortiz A (Ed) Collaborative networks and their breeding environments. Springer, New York
Ivanov D, Kaeschel J, Arkhipov A, Sokolov B (2006) A conceptual framework for modeling complex adaptation of collaborative networks. In: Proceedings of the 7th international conference on virtual enterprises. Helsinki, 25-27 September.
Ivanov D, Arkhipov A, Sokolov B (2007a) Intelligent planning and control of manufacturing supply chains in virtual enterprises. Int J Manuf Tech Manag 11(2):209–227
Ivanov D, Kaeschel J, Sokolov B (2007b) Integrated modeling of agile enterprise networks. International Journal of Agile Systems and Management 2(1):23–49
Ivanov D, Sokolov B, Kaeschel J (2010) A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations. Eur J Oper Res. 200: 409–420
Kaihara T (2004) Enterprise negotiation algorithm with walrasian virtual market. In: Camarihna-Matos L (Ed) Virtual enterprises and collaborative networks. Kluwer Academic Publishers, Boston
Kalinin VN (1982) The problem of optimal control of active moving objects. Differ Equat 17(2):1350–1355
Kalinin VN, Sokolov BV (1985) Optimal planning of the process of interaction of moving operating objects. Differ Equat 21(5):502–506
Kalinin VN, Sokolov BV (1987) A dynamic model and an optimal scheduling algorithm for activities with bans of interrupts. Autom Rem Contr 48(1-2):88–94
Kalinin VN, Sokolov BV (1996) Multiple-model description of control processes for airspace crafts. J Comput Syst Sci Int 6:192–199
Kuehnle H (2008) A system of models contribution to production network (PN) theory. J Intell Manuf 18(5):543–551
Mesarovic MD and Takahara Y (1975) General systems theory: mathematical foundations. Academic Press, New York, Can Francisco, London.
Muriel A and Simchi-Levi D (2004) Supply chain design and planning – application of optimization techniques for strategic and tactical models. In: Kok de AG, Graves SC (Ed) Supply chain management: design, coordination and operation. Amsterdam, Elsevier
Okhtilev M, Sokolov B, Yusupov R (2006) Intelligent technologies of complex systems monitoring and structure dynamics control. Nauka, Moscow (in Russian)
Sokolov BV, Yusupov RM (2004) Conceptual foundations of quality estimation and analysis for models and multiple-model systems. J Comput Syst Sci Int 6:5–16
Rights and permissions
Copyright information
© 2010 Springer-Verlag London Limited
About this chapter
Cite this chapter
(2010). DIMA – Decentralized Integrated Modelling Approach. In: Adaptive Supply Chain Management. Springer, London. https://doi.org/10.1007/978-1-84882-952-7_9
Download citation
DOI: https://doi.org/10.1007/978-1-84882-952-7_9
Publisher Name: Springer, London
Print ISBN: 978-1-84882-951-0
Online ISBN: 978-1-84882-952-7
eBook Packages: EngineeringEngineering (R0)