A simulation-based decision support framework for real-time supply chain risk management

References

• Tang C, Tomlin B. The power of flexibility for mitigating supply chain risks. Int J Prod Econ. 2008;116(1):12–27.10.1016/j.ijpe.2008.07.008
   Web of Science ®Google Scholar
• Chisropher M, Peck H. Building the resilient supply chain. Int J Logistics Manage. 2004;15(2):1–13.
   Google Scholar
• Singhal P, Agarwal G, Mittal ML. Supply chain risk management: review, classification and future research directions. Int J Bus Sci Appl Manage. 2011;6(3):15–42.
   Google Scholar
• Norrman A, Jansson U. Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident. Int J Phys Distrib Logistics Manage. 2004;34(5):434–456.10.1108/09600030410545463
   Google Scholar
• Jüttner U. Supply chain risk management: understanding the business requirements from a practitioner perspective. Int J Logistics Manage. 2005;16(1):120–141.10.1108/09574090510617385
   Google Scholar
• Hallikas J, Karvonen I, Pulkkinen U, Virolainen V, Tuominen M. Risk management processes in supplier networks. Int J Prod Econ. 2004;90(1):47–58.10.1016/j.ijpe.2004.02.007
   Web of Science ®Google Scholar
• Tuncel G, Alpan G. Risk assessment and management for supply chain networks: a case study. Comput Ind. 2010;61(3):250–259.10.1016/j.compind.2009.09.008
   Web of Science ®Google Scholar
• Sahay BS, Ranjan J. Real time business intelligence in supply chain analytics. Inf Manage Comput Secur. 2008;16(1):28–48.
   Google Scholar
• Ghadge A, Dani S, Chester M, Kalawsky R. A systems approach for modelling supply chain risks. Supply Chain Manage: An Int J. 2013;18(5):523–538.10.1108/SCM-11-2012-0366
   Web of Science ®Google Scholar
• Chen X, Ong YS, Tan PS, Zhang N, Li Z. Agent-based modeling and simulation for supply chain risk management – a survey of the State-of the-Art. 2013 IEEE International Conference on Systems, Man, and Cybernetics; 2013; Manchester, United Kingdom.
   Google Scholar
• Wu T, Huang S, Blackhurst J, Zhang X, Wang S. Supply chain risk management: an agent-based simulation to study the impact of retail stockouts. IEEE Trans Eng Manage. 2013;60:676–686.
   Google Scholar
• Holcomb MC, Ponomarov SY, Manrodt KB. The Relationship of supply chain visibility to firm performance. Supply Chain Forum: An Int J. 2011;60(4):32–45.
   Google Scholar
• Gattorna J. Supply chain alignment. Franham, UK: Gower publishing; 2009.
   Google Scholar
• Goh M, De Souza R, Zhang AN, He W, Tan PS. Supply chain visibility: a decision making perspective. 4th IEEE Conference on Industrial Electronics and Applications; 2009 May 25–27; Xian, China: 2546–2551.
   Google Scholar
• Caridi M, Moretto A, Perego A, Tumino A. The benefits of supply chain visibility: a value assessment model. Int J Prod Econ. 2014;151:1–19.10.1016/j.ijpe.2013.12.025
   Web of Science ®Google Scholar
• Geerts GL, O’Leary DE. A supply chain of things: the EAGLET ontology for highly visible supply chains. Decis Support Syst. 2014;63:3–22.10.1016/j.dss.2013.09.007
   Web of Science ®Google Scholar
• March J, Shapira Z. Managerial perspectives on risk and risk taking. Manage Sci. 1987;33(11):1404–1418.10.1287/mnsc.33.11.1404
   Web of Science ®Google Scholar
• Yates JF, Stone ER. The risk construct. In: Yates JF, editor. Risk taking behavior. New York, NY: Wiley; 1992. p. 1–25.
   Google Scholar
• Wang Z, Yin X, Fu X, Ponnambalam L, Lu S. Riskvis: supply chain visualization with risk management and real-time monitoring. 2013 IEEE International Conference on Automation Science and Engineering; 2013 August 17–20; Madison, WI, USA.
   Google Scholar
• Heer J, Shneiderman B. Interactive dynamics for visual analysis. Mag Commun ACM. 2012;55(4):45–54.10.1145/2133806
   Web of Science ®Google Scholar
• Krmac EV. Intelligent value chain networks: business intelligence and other ICT tools and technologies in supply/demand chains. In: Renko S, editor. Supply chain management - new perspectives. Rijeka, Croatia: InTech; 2011. p. 581–614.
   Google Scholar
• Kursan I, Mihic M. Business intelligence: the role of the Internet in marketing research and business decision making. Management. 2015;15(1):69–86.
   Google Scholar
• Hegmanns T, Schwede C, Motta M, Henke M. Model-based technologies for tool support in supply chain risk management. 7th International Scientific Symposium on Logistics; 2014 June 4–5; Cologne.
   Google Scholar
• Mele FD, Guillen G, Espuna A, Puigjaner L. A simulation-based optimization framework for parameter optimization of supply-chain networks. Ind Eng Chem Res. 2006;45:3133–3148.10.1021/ie051121g
   Web of Science ®Google Scholar
• Banks J. Introduction to simulation. Proceedings of the 32nd conference on Winter simulation; 2000 December 10–13; Orlando, FL, USA.
   Google Scholar
• van der Zee DJ, van der Vorst JGAJ. A modeling framework for supply chain simulation: opportunities for improved decision making. Decis Sci. 2005;36(1):65–95.10.1111/deci.2005.36.issue-1
   Web of Science ®Google Scholar
• Long Q. An agent-based distributed computational experiment framework for virtual supply chain network development. Expert Syst Appl. 2014;41(9):4094–4112.10.1016/j.eswa.2014.01.001
   Web of Science ®Google Scholar
• Macal CM, North MJ. Tutorial on agent-based modelling and simulation. J Simul. 2010;4:151–162.10.1057/jos.2010.3
   Web of Science ®Google Scholar
• Giannakis M, Louis M. A multi-agent based framework for supply chain risk management. J Purch Supply Manage. 2011;17:23–31.10.1016/j.pursup.2010.05.001
   Web of Science ®Google Scholar
• Bigus JP, Bigus J. Constructing intelligent agents using JavaTM. 2nd ed. New York, NY: John Wiley & Sons; 2001.
   Google Scholar
• Glinz M. An Integrated formal model of scenarios based on statecharts. Proceedings of the 5th European Software Engineering Conferenc; 1995 September 25–28; Sitges, Spain: 254–271.
   Google Scholar
• Bauer B, Odell J. UML 2.0 and agents: how to build agent-based systems with the new UML standard. Eng Appl Artif Intell. 2005;141–157.10.1016/j.engappai.2004.11.016
   Web of Science ®Google Scholar
• Fox MS, Barbuceanu M, Teigen R. Agent-oriented supply-chain management. Int J Flexible Manuf Syst. 2000;12(2/3):165–188.10.1023/A:1008195614074
   Web of Science ®Google Scholar
• Güller M, Hegmanns T. Simulation-based performance analysis of a miniload multishuttle order picking system. In: ElMaraghy H, editor. Proceedings of the 47th CIRP Conference on Manufacturing Systems; 2014 April 28–30; Windsor, Canada. Springer. p. 475–480.
   Google Scholar
• Winsper M, Chli M. Decentralized supply chain formation using max-sum loopy belief. Comput Intell. 2012;29(2):281–309.
   Web of Science ®Google Scholar
• Srinivas N, Harding JA. A data mining integrated architecture for shop floor control. J Eng Manuf. 2008;222(5):605–624.10.1243/09544054JEM980
   Web of Science ®Google Scholar
• Harper TJ. Agent based modeling and simulation framework for supply chain risk management [dissertation]. Ohio, USA: Air Force Institute of Technology; 2012.
   Google Scholar
• Geng L, Xiao R, Xu X. Research on MAS-based supply chain resilience and its self-organized criticality. Discrete Dyn Nat Soc. 2014;2014: 1–14.10.1155/2014/621341
   Web of Science ®Google Scholar
• Jager W. Simulating consumer behaviour: a perspective. In Workshop Environmental policy and evolutionary economic modelling; 2006 May 18; Amsterdam.
   Google Scholar