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International Conference on Dynamics in Logistics

LDIC 2018: Dynamics in Logistics pp 34–39Cite as

Simulation Vs. Optimization Approaches to Ripple Effect Modelling in the Supply Chain

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Part of the book series: Lecture Notes in Logistics ((LNLO))

Abstract

As a result of supply chain structural dynamics, the ripple effect occurs whereby disruption propagates downstream or upstream from the initial disturbance point in the network. Since ripple effect analysis includes both dynamic and static parametrical sets, the research objective of this study is to identify recommendations on the preferable applications of simulation and optimization methods. We identify some problem classes and datasets for which optimization, simulation, and hybrid optimization-simulation methods can be recommended.

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References

  • Carvalho, H., Barroso, A.P., Machado, V.H., Azevedo, S., Cruz-Machado, V.: Supply chain redesign for resilience using simulation. Comp. Ind. Eng. 62(1), 329–341 (2012)

    Article  Google Scholar 

  • Dolgui, A., Ivanov, D., Sokolov, B.: Ripple effect in the supply chain: an analysis and recent literature. Int. J. Prod. Res. (2018, published online). https://doi.org/10.1080/00207543.2017.1387680

  • Frazzon, E.M., Albrecht, A., Pires, M.C., Israel, E., Kück, M., Freitag, M.: Hybrid approach for the integrated scheduling of production and transport processes along supply chains. Int. J. Prod. Res. (2017). https://doi.org/10.1080/00207543.2017.1355118

  • Hasani, A., Khosrojerdi, A.: Robust global supply chain network design under disruption and uncertainty considering resilience strategies: a parallel memetic algorithm for a real-life case study. Transp. Res. Part E Logist. Transp. Rev. 87, 20–52 (2016)

    Article  Google Scholar 

  • Ho, W., Zheng, T., Yildiz, H., Talluri, S.: Supply chain risk management: a literature review. Int. J. Prod. Res. 53(16), 5031–5069 (2015)

    Article  Google Scholar 

  • Ivanov, D.: Structural Dynamics and Resilience in Supply Chain Risk Management. Springer, New York (2018)

    Book  Google Scholar 

  • Ivanov, D., Rozhkov, M.: Coordination of production and ordering policies under capacity disruption and product write-off risk: an analytical study with real-data based simulations of a fast moving consumer goods company. Ann. Oper. Res. (2017, published online). https://doi.org/10.1007/s10479-017-2643-8

  • Ivanov, D.: Simulation-based ripple effect modelling in the supply chain. Int. J. Prod. Res. 55(7), 2083–2101 (2017)

    Article  Google Scholar 

  • Ivanov, D., Pavlov, A., Pavlov, D., Sokolov, B.: Minimization of disruption-related return flows in the supply chain. Int. J. Prod. Econ. 183, 503–513 (2017b)

    Article  Google Scholar 

  • Ivanov, D., Sokolov, B., Dolgui, A.: The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management. Int. J. Prod. Res. 52(7), 2154–2172 (2014a)

    Article  Google Scholar 

  • Ivanov, D., Sokolov, B., Pavlov, A., Dolgui, A., Pavlov, D.: Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies. Transp. Res. Part E 90, 7–24 (2016)

    Article  Google Scholar 

  • Ivanov, D., Sokolov, B., Pavlov, A.: Optimal distribution (re)planning in a centralized multi-stage network under conditions of ripple effect and structure dynamics. Eur. J. Oper. Res. 237(2), 758–770 (2014b)

    Article  MathSciNet  MATH  Google Scholar 

  • Ivanov, D., Tsipoulanidis, A., Schönberger, J.: Global Supply Chain and Operations Management, 1st edn. Springer, Cham (2017a)

    Book  MATH  Google Scholar 

  • Ivanov, D., Dolgui, A., Sokolov, B., Ivanova, M.: Literature review on disruption recovery in the supply chain. Int. J. Prod. Res. 55(20), 6158–6174 (2017c)

    Article  Google Scholar 

  • Ivanov, D., Sokolov, B., Kaeschel J.: A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations. Eur. J. Oper. Res. 200(2), 409–420 (2010)

    Article  MATH  Google Scholar 

  • Klibi, W., Martel, A.: Modeling approaches for the design of resilient supply networks under disruptions. Int. J. Prod. Econ. 135(2), 882–898 (2012)

    Article  Google Scholar 

  • Liberatore, F., Scaparra, M.P., Daskin, M.S.: Hedging against disruptions with ripple effects in location analysis. Omega 40, 21–30 (2012)

    Article  Google Scholar 

  • Lim, M., Daskin, M.S., Bassamboo, A., Chopra, S.: A facility reliability problem: formulation, properties and algorithm. Nav. Res. Logist. 57(1), 58–70 (2010)

    MathSciNet  MATH  Google Scholar 

  • Paul, S.K., Sarker, R., Essam, D.: Real time disruption management for a two-stage batch production–inventory system with reliability considerations. Eur. J. Oper. Res. 237, 113–128 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  • Rezapour, S., Farahani, R., Pourakbar, M.: Resilient supply chain network design under competition: a case study. Eur. J. Oper. Res. 259(3), 1017–1035 (2017)

    Article  MathSciNet  Google Scholar 

  • Sawik, T.: Integrated selection of suppliers and scheduling of customer orders in the presence of supply chain disruption risks. Int. J. Prod. Res. 51(23–24), 7006–7022 (2013)

    Article  Google Scholar 

  • Sawik, T.: A portfolio approach to supply chain disruption management. Int. J. Prod. Res. 55(7), 1970–1991 (2017)

    Article  Google Scholar 

  • Scheibe, K.P., Blackhurst, J.: Supply chain disruption propagation: a systemic risk and normal accident theory perspective. Int. J. Prod. Res. (2017). https://doi.org/10.1080/00207543.2017.1355123

  • Schmitt, A.J., Singh, M.: A quantitative analysis of disruption risk in a multi-echelon supply chain. Int. J. Prod. Econ. 139(1), 23–32 (2012)

    Article  Google Scholar 

  • Schmitt, T.G., Kumar, S., Stecke, K.E., Glover, F.W., Ehlen, M.A.: Mitigating disruptions in a multi-echelon supply chain using adaptive ordering. Omega 68, 185–198 (2017)

    Article  Google Scholar 

  • Snyder, L.V., Zümbül, A., Peng, P., Ying, R., Schmitt, A.J., Sinsoysal, B.: OR/MS models for supply chain disruptions: a review. IIE Trans. 48(2), 89–109 (2016)

    Article  Google Scholar 

  • Snyder, L.V., Daskin, M.S.: Reliability models for facility location: the expected failure cost case. Transp. Sci. 39, 400–416 (2005)

    Article  Google Scholar 

  • Tang, C.S.: Perspectives in supply chain risk management. Int. J. Prod. Econ. 103, 451–488 (2006)

    Article  Google Scholar 

  • Torabi, S.A., Baghersad, M., Mansouri, S.A.: Resilient supplier selection and order allocation under operational and disruption risks. Transp. Res. Part E Logist. Transp. Rev. 79, 22–48 (2015)

    Article  Google Scholar 

  • Vahdani, B., Zandieh, M., Roshanaei, V.: A hybrid multi-stage predictive model for supply chain network collapse recovery analysis: a practical framework for effective supply chain network continuity management. Int. J. Prod. Res. 49(7), 2035–2060 (2011)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Business and Economics, Berlin School of Economics and Law, Badensche Str. 50, 10825, Berlin, Germany

    Dmitry Ivanov & Marina Ivanova

  2. Automation, Production and Computer Sciences Department, IMT Atlantique LS2N - CNRS UMR 6004, La Chantrerie, Nantes, France

    Alexandre Dolgui

  3. Saint Petersburg Institute for Informatics and Automation of the RAS (SPIIRAS), V.O. 14 line, 39, 199178, St. Petersburg, Russia

    Boris Sokolov

Authors
  1. Dmitry Ivanov
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  2. Alexandre Dolgui
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  3. Marina Ivanova
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  4. Boris Sokolov
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Corresponding author

Correspondence to Dmitry Ivanov .

Editor information

Editors and Affiliations

  1. Fachbereich 4 - Produktionstechnik, Universität Bremen, Bremen, Germany

    Michael Freitag

  2. Fachbereich 7 - Wirtschaftswissenschaft, Universität Bremen, Bremen, Bremen, Germany

    Herbert Kotzab

  3. Fachbereich 4 - Produktionstechnik, Universität Bremen, Bremen, Germany

    Jürgen Pannek

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Ivanov, D., Dolgui, A., Ivanova, M., Sokolov, B. (2018). Simulation Vs. Optimization Approaches to Ripple Effect Modelling in the Supply Chain. In: Freitag, M., Kotzab, H., Pannek, J. (eds) Dynamics in Logistics. LDIC 2018. Lecture Notes in Logistics. Springer, Cham. https://doi.org/10.1007/978-3-319-74225-0_5

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  • DOI: https://doi.org/10.1007/978-3-319-74225-0_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74224-3

  • Online ISBN: 978-3-319-74225-0

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