Environment Systems & Decisions

, Volume 33, Issue 1, pp 104–120 | Cite as

Design for resilience in infrastructure distribution networks

Article

Abstract

The recognition that resilience is a critical aspect of infrastructure security has caused the national and homeland security communities to ask “How does one ensure infrastructure resilience?” Previous network resilience analysis methods have generally focused on either pre-disruption prevention investments or post-disruption recovery strategies. This paper expands on those methods by introducing a stochastic optimization model for designing network infrastructure resilience that simultaneously considers pre- and post-disruption activities. The model seeks investment–recovery combinations that minimize the overall cost to a distribution network across a set of disruption scenarios. A set of numerical experiments illustrates how changes to disruption scenarios probabilities affect the optimal resilient design investments.

Keywords

Resilience Network optimization Infrastructures Investment Design 

References

  1. Barroso AP, Machado VH, Machado VC (2011) The resilience paradigm in the supply chain management: a case study. IEEE Int Conf Ind Eng Eng Manage 2011:928–932Google Scholar
  2. Bell MGH, Iida Y (eds) (2003) The network reliability of transport. Pergamon, OxfordGoogle Scholar
  3. Bell MGH, Kanturska U, Schmocker J-D, Fonzone A (2008) Attacker-defender models and road network vulnerability. Philos Transact R Soc A Math Phys Eng Sci 366(1872):1893–1906CrossRefGoogle Scholar
  4. Birge JR, Louveaux FV (1997) Introduction to stochastic programming. Springer, New YorkGoogle Scholar
  5. Bush GW (2002) Homeland security presidential directive-3 (HSPD-3). Washington, DCGoogle Scholar
  6. Bush GW (2003) Homeland security presidential directive-7 (HSPD-7). Washington, DCGoogle Scholar
  7. Chassin DP, Posse C (2005) Evaluating North American grid reliability using the Barabasi-Albert network model. Phys A 355:667–677CrossRefGoogle Scholar
  8. Chen L, Miller-Hooks E (2012) Resilience: an indicator of recovery capability in intermodal freight transport. Transport Sci 46(1):109–123CrossRefGoogle Scholar
  9. Chen A, Kongsamsaksakul S, Zhou Z, Lee M, Recker W (2007) Assessing network vulnerability of degradable transportation systems: an accessibility based approach. In: Allsop RE, Bell MGH, Heydecker BG (eds) Transportation and traffic theory 2007. Elsevier, Oxford, pp 235–262Google Scholar
  10. Clausen J, Larsen A, Larsen J, Rezanova NJ (2010) Disruption management in the airline industry—concepts. Models Methods Comput Operat Res 37:809–821Google Scholar
  11. Clinton W (1998) Presidential decision directive PDD-63. Protecting America’s Critical Infrastructures, Washington, DCGoogle Scholar
  12. Croope S, McNeil S (2011) Improving resilience of critical infrastructure systems postdisaster: recovery and mitigation. Transp Res Rec 2234:3–13CrossRefGoogle Scholar
  13. Fiksel J (2003) Designing resilient, sustainable systems. Environ Sci Technol 37(23):5330–5339CrossRefGoogle Scholar
  14. Guercio R, Xu Z (1997) Linearized optimization model for reliability-based design of water systems. J Hydraul Eng 123(11):1020–1026CrossRefGoogle Scholar
  15. Haimes Y (2009) On the definition of resilience in systems. Risk Anal 29(4):498–501CrossRefGoogle Scholar
  16. Heydecker B, Lam WHK, Zhang N (2007) Use of travel demand satisfaction to assess road network reliability. Transportmetrica 3(2):139–171CrossRefGoogle Scholar
  17. Jenelius E, Petersen T, Mattsson LG (2006) Road network vulnerability: identifying important links and exposed regions. Transport Res A 20:537–560Google Scholar
  18. Kall P, Wallace SW (1994) Stochastic programming. Wiley, ChichesterGoogle Scholar
  19. Khandani AE, Abounadi J, Modiano E, Zheng L (2008) Reliability and route diversity in wireless networks. IEEE Trans Wireless Commun 7(12):4772–4776CrossRefGoogle Scholar
  20. Klau GW, Weiskircher R (2005) Robustness and resilience. In: Brandes U, Erlebach T (eds) Network analysis., Lecture Notes in Computer Science, 3418Springer, Berlin, pp 417–437CrossRefGoogle Scholar
  21. Lindo Systems, Inc (2010) Lingo—optimization modeling software for linear. Nonlinear and Integer Programming, Chicago, ILGoogle Scholar
  22. Little RG (2002) Toward more robust infrastructure: observations on improving the resilience and reliability of critical systems. In: Proceedings of the 36th Hawaii international conference on systems sciences, Kauai, HawaiiGoogle Scholar
  23. Lou Y, Zhang L (2011) Defending transportation networks against random and targeted attacks. Transp Res Rec 2234:31–40CrossRefGoogle Scholar
  24. Luna R, Balakrishnan N, Dagli CH (2011) Postearthquake recovery of a water distribution system: discrete event simulation using colored petri nets. J Infrastruct Syst Am Soc Civil Eng 17:25–34CrossRefGoogle Scholar
  25. Mansouri M, Nilchiana R, Mostashari A (2010) A policy making framework for resilient port infrastructure systems. Marine Policy 34(6):1125–1134CrossRefGoogle Scholar
  26. Merrel SA, Moore AP, Stevens JF (2010) Goal-based assessment for the cybersecurity of critical infrastructure. IEEE Int Conf Tech Homel Sec 2010:84–88Google Scholar
  27. Murray-Tuite PM, Mahmassani HS (2004) Methodology for determining vulnerable links in a transportation network. Transp Res Rec 1882:88–96CrossRefGoogle Scholar
  28. Obama B (2011) Presidential policy directive 8: national preparedness. http://www.dhs.gov/presidential-policy-directive-8-national-preparedness. Accessed July 9, 2012
  29. Park J, Seager TP, Rao PSC, Convertino M, Linkoz I (2012) Integrating risk and resilience approaches to catastrophe management in engineering systems, risk analysis. doi:10.1111/j.1539-6924.2012.01885.x
  30. Petersen KE, Johansson H (2008) Designing resilient critical infrastructure systems using risk and vulnerability analysis. In: Hollnagel E, Nemeth CP, Dekker S (eds) Resilience engineering perspectives. Ashgate Publishers, Farnham, pp 160–171Google Scholar
  31. Petit TJ, Fiksel J, Croxton KL (2010) Ensuring supply chain resilience: development of a conceptual framework. J Bus Logist 31(1):1–21CrossRefGoogle Scholar
  32. Ponomorov SY, Holcomb MC (2009) Understanding the concept of supply chain resilience. Int J Logist Manage 20(1):124–143CrossRefGoogle Scholar
  33. Qiang Q, Nagurney A (2008) A unified network performance measure with importance identification and the ranking of network components. Optim Lett 2:127–142CrossRefGoogle Scholar
  34. Reagan R (1982) Executive order 13282. National Security Telecommunications Advisory Committee, Washington, DCGoogle Scholar
  35. Salami O, Bagula A, Chan HA (2011) Framework for link reliability in inter-working multi-hop wireless networks. Mathem Comput Modell 53:2219–2228CrossRefGoogle Scholar
  36. Scott DM, Novak DC, Aultman-Hall L, Guo F (2006) Network Robustness Index: a new method for identifying critical links and evaluating the performance of transportation networks. J Transp Geogr 14(3):215–227CrossRefGoogle Scholar
  37. Sherali HD, Dalkiran E, Glickman TS (2011) Selecting optimal alternatives and risk reduction strategies in decision trees. Operat Res 59(3):631–647CrossRefGoogle Scholar
  38. Shinstine DS, Ahmed I, Lansey KE (2002) Reliability/availability analysis of municipal water distribution networks: case studies. J Water Res Plann Manage 128(2):140–151CrossRefGoogle Scholar
  39. Soni U, Jain V (2011) Minimizing the vulnerabilities of supply chain: a new framework for enhancing the resilience. IEEE Int Conf Ind Eng Eng Manage 2011:933–939Google Scholar
  40. Suribabu CR, Neelakantan TR (2008) Reliability based optimal design of water distribution network by genetic algorithm. J Intell Syst 17(1–3):143–156Google Scholar
  41. U.S. Department of Homeland Security (2009) National infrastructure protection plan. Washington, DCGoogle Scholar
  42. Vaze R, Heath RW (2008) Maximizing reliability in multi-hop wireless networks, ISIT 2008. In: Proceedings of the IEEE international symposium on information theory, Toronto, Ontario, pp 11–15Google Scholar
  43. Vugrin ED, Camphouse RC (2011) Infrastructure resilience assessment through control design. Int J Crit Infrast 7(3):243–260CrossRefGoogle Scholar
  44. Vugrin ED, Warren DE, Ehlen MA, Camphouse RC (2010) A framework for assessing the resilience of infrastructure and economic systems. In: Gopalakrishnan K, Peeta S (eds) Sustainable and resilient critical infrastructure systems: simulation, modeling, and intelligent engineering. Springerg, Berlin, pp 77–116CrossRefGoogle Scholar
  45. Wang N, Fagear A, Pavlou G (2011) Adaptive post-failure load balancing in fast reroute enabled IP networks. In: Proceedings of the 12th IFIP/IEEE international symposium on integrated network management, IM 2011, pp 470–477Google Scholar
  46. Xu N, Guikema SD, Davidson RA, Nozick LK, Çağnan Z, Vaziri K (2007) Optimizing scheduling of post-earthquake electric power restoration tasks. Earthquake Eng Struct Dynam 36:265–284CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside the USA) 2013

Authors and Affiliations

  1. 1.Sandia National LaboratoriesAlbuquerqueUSA
  2. 2.Cornell UniversityIthacaUSA

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