Abstract
In recent years, the works on supply chain management (SCM) have been broadened from isolated static models of supply chain design (SCD) and planning (SCP) to integrated SCD and SCP models. This paper develops a framework for integrated SCD and SCP on the basis of adaptation principles and regarding SC execution dynamics. To achieve this integration, static models of SCD are brought in correspondence to the dynamic models of SCP and control. The adaptive feedback loops between the planning and execution models are established. It becomes possible if traditional operations research (OR) techniques are extended by optimal control theory. We illustrate the general framework with the help of a modelling complex. We show explicitly how to distribute static and dynamics variables and constraints of SCD and SCP by interconnecting static elements in SCD optimization linear programming model with corresponding SCP dynamic elements in optimal control model. This makes it possible to consider conventionally isolated SCD and SCP problems taking into account non-stationarity of supply chain execution along with the adaptive control within a conceptually and mathematically integrated framework. In doing so, the developed framework contributes to the advancing decision-making support for SCM on the basis of interrelating planning and execution levels instead of generating optimal solutions that fail in a real perturbed execution environment.
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References
Ahn, H.J., Lee, H., Park, S.J.: A flexible agent system for change adaptation in supply chains. Expert Syst. Appl. 25, 603–618 (2003)
Casti, J.L.: Connectivity, complexity and catastrophe in large-scale systems. Wiley Interscience, New York (1979)
Chandra, C., Grabis, J.: Supply chain configuration. Springer, New York (2007)
Chauhan, S.S., Gordon, V., Proth, J.M.: Scheduling in supply chain environment. Eur. J Oper. Res. 183(3), 961–970 (2007)
Choi, T.Y., Dooley, K.J., Rungtusanatham, M.: Supply networks and complex adaptive systems: control versus emergence. J Oper. Manag. 19(3), 351–366 (2001)
Chopra, S., Meindl, P.: Supply chain management. Strategy, planning and operation. Pearson Prentice Hall, New Jersey (2007)
Disney, S.M., Towill, D.R., Warburton, R.D.H.: On the equivalence of control theoretic, differential, and difference equation approaches to modeling supply chains. Int. J. Prod. Econ. 101, 194–208 (2006)
Disney, S.M., Towill, D.R.: A discrete linear control theory model to determine the dynamic stability of Vendor Managed Inventory supply chains. Int. J. Prod. Res. 40(1), 179–204 (2002)
Dolgui, A., Proth, J.M.: Supply Chains Engineering: useful methods and techniques. Springer, Berlin (2009)
Geoffrion, A., Graves, G.: Multicommodity distribution system design by Benders decomposition. Manag. Sci. 29(5), 822–844 (1974)
Harrison, T.P.: Principles for the strategic design of supply chains. In: The practice of supply chain management. Kluwer Academic Publishers, Boston (2005)
Hentsch, K., Koechel, P.: Scheduling jobs with forbidden setups with metaheuristics and penalties – a case study at a continuous casting plant. In: Proceeding of the 10th International Symposium on Operational Research, Slovenia, pp. 259–268 (2009)
Ivanov, D.: DIMA – A Research Methodology for Comprehensive Multi Disciplinary Modelling of Production and Logistics Networks. Int. J. Prod. Res. 47(5), 1133–1155 (2009a)
Ivanov, D.: Adaptive aligning of planning decisions on supply chain strategy, design, tactics, and operations. Int. J. Prod. Res. (2009b), doi:10.1080/002075409028935417 (in press)
Ivanov, D., Sokolov, B.: Adaptive Supply Chain Management. Springer, London (2010)
Ivanov, D., Arkhipov, A., Sokolov, B.: Intelligent planning and control of manufacturing supply chains in virtual enterprises. Int. J. Manuf. Tech. Manag. 11(2), 209–227 (2007)
Ivanov, D., Kaeschel, J., Sokolov, B.: Structure dynamics control-based framework for adaptive reconfiguration of collaborative enterprise networks. Int. J Manuf. Techn. and Manag. 17(1-2), 3–41 (2009)
Ivanov, D., Sokolov, B., Kaeschel, J.: A multi-structural framework for adaptive supply chain planning and operations with structure dynamics considerations. Eur. J. Oper. Res. 200, 409–420 (2010)
Jang, P.Y.: A flexible and adaptive control architecture for the efficient supply chain management (SCM). WSEAS Transactions on Communications 5(6), 1015–1025 (2006)
Gunasekaran, A., Kee-hung, L., Cheng, T.C.E.: Responsive supply chain: a competitive strategy in a networked economy. Omega 36(4), 549–564 (2008)
Kim, C.O., Jun, J., Baek, J.K., Smith, R.L., Kim, Y.D.: Adaptive inventory control models for supply chain management. Int. J. Adv. Manuf. Tech. 26(9-10), 1184–1192 (2005)
Kreipl, S., Pinedo, M.: Planning and Scheduling in Supply Chains: An Overview of Issues in Practice. Prod. Oper. Manag. 13(1), 77–92 (2004)
Lalwani, C.S., Disney, S., Towill, D.R.: Controllable, observable and stable state space representations of a generalized order-up-to policy. Int. J. Prod. Econ. 101, 172–184 (2006)
Mesarovic, M.D., Takahara, Y.: General systems theory: mathematical foundations. Academic Press, London (1975)
Moskvin, B.V.: Optimization of information transmission in packet network. In: Trans. of All-Union conf. “Compac 87”, Riga, pp. 168–171 (1987)
Müller, E., Horbach, S., Ackermann, J.: Integrative planning and design of logistics structures and production plants in Competence-cell-based networks. Int. J. Services Oper. Informatics 3(1), 40–52 (2008)
Okhtilev, M., Sokolov, B., Yusupov, R.: Intelligent technologies of complex systems monitoring and structure dynamics control, Nauka, Moskau (2006)
Peck, H.: Supply Chain Vulnerability, Risk, Robustness, and Resilience. In: Global Logistics and Supply Chain management, pp. 229–248. John Wiley and Sons, Chichester (2007)
Shen, Z.M.: Integrated supply chain design models: a survey and feature research directions. J Ind. Manag. Optim. 3(1), 1–27 (2007)
Shervais, S., Shannon, T.T., Lendaris, G.G.: Intelligent supply chain management using adaptive critic learning. IEEE Trans. Syst. Man. Cybern. Syst. Hum. 33(2), 235–244 (2003)
Scholz-Reiter, B., Hoehns, H., Hamann, T.: Adaptive control of supply chains: building blocks and tools of an agent-based simulation framework. CIRP Annals Manufacturing Technology 53(1), 353–356 (2004)
Sethi, S.P., Thompson, G.L.: Optimal Control Theory: Applications to Management Science and Economics. Springer, Berlin (2006)
Simchi-Levi, D., Wu, S.D., Zuo-Yun, S.: Handbook of quantitative supply chain analysis. Springer, New York (2004)
Skurihin, V.I., Zabrodsky, V.A., Kopeychenko, Y.V.: Adaptive control systems in machinery industry. Mashinostroenie, Moscow (1989)
Sokolov, B.V., Yusupov, R.M.: Conceptual foundations of quality estimation and analysis for models and multiple-model systems. Int. J. Comput. Syst. Sci. 6, 5–16 (2004)
Surana, A., Kumara, S., Greaves, M., Raghavan, U.N.: Supply-chain networks: a complex adaptive systems perspective. Int. J. Prod. Res. 43(20), 4235–4265 (2005)
Van Houtum, G.Y., Scheller-Wolf, A., Yi, J.: Optimal Control of Serial Inventory Systems with Fixed Replenishment Intervals. Oper. Res. 55(4) (2007)
Van de Vonder, S., Demeulemeester, E., Herroelen, W.: A classification of predictive-reactive project scheduling procedures. Journal of Scheduling 10(3), 195–207 (2007)
Vidal, C., Goetschalckx, M.: Strategic production-distribution models: a critical review with emphasis on global supply chain models. Eur. J. Oper. Res. 98, 1–18 (1997)
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Ivanov, D., Sokolov, B., Kaeschel, J. (2010). Integrated Adaptive Design and Planning of Supply Networks. In: Dangelmaier, W., Blecken, A., Delius, R., Klöpfer, S. (eds) Advanced Manufacturing and Sustainable Logistics. IHNS 2010. Lecture Notes in Business Information Processing, vol 46. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12494-5_14
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DOI: https://doi.org/10.1007/978-3-642-12494-5_14
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