Probability Distributions on Partially Ordered Sets and Network Interdiction Games

Published Online:https://doi.org/10.1287/moor.2021.1140

References

  • [1] Adler I, Monteiro RDC (1992) A geometric view of parametric linear programming. Algorithmica 8(1):161–176.CrossrefGoogle Scholar
  • [2] Ahuja RK, Magnanti TL, Orlin JB (1993) Network Flows: Theory, Algorithms, and Applications (Prentice Hall, Upper Saddle River, NJ).Google Scholar
  • [3] Aneja YP, Chandrasekaran R, Nair KPK (2001) Maximizing residual flow under an arc destruction. Networks 38(4):194–198.CrossrefGoogle Scholar
  • [4] Assadi S, Emamjomeh-Zadeh E, Norouzi-Fard A, Yazdanbod S, Zarrabi-Zadeh H (2014) The minimum vulnerability problem. Algorithmica 70(4):718–731.CrossrefGoogle Scholar
  • [5] Assimakopoulos N (1987) A network interdiction model for hospital infection control. Comput. Biology Medicine 17(6):413–422.CrossrefGoogle Scholar
  • [6] Avenhaus R, Canty MJ (2009) Inspection games. Meyers RA, ed. Encyclopedia of Complexity and Systems Science (Springer, New York), 4855–4868.CrossrefGoogle Scholar
  • [7] Balinski M, Tucker A (1969) Duality theory of linear programs: A constructive approach with applications. SIAM Rev. 11(3):347–377.CrossrefGoogle Scholar
  • [8] Ball MO, Golden BL, Vohra RV (1989) Finding the most vital arcs in a network. Oper. Res. Lett. 8(2):73–76.CrossrefGoogle Scholar
  • [9] Baykal-Gürsoy M, Duan Z, Poor HV, Garnaev A (2014) Infrastructure security games. Eur. J. Oper. Res. 239(2):469–478.CrossrefGoogle Scholar
  • [10] Bertsimas D, Nasrabadi E, Orlin JB (2016) On the power of randomization in network interdiction. Oper. Res. Lett. 44(1):114–120.CrossrefGoogle Scholar
  • [11] Bertsimas D, Nasrabadi E, Stiller S (2013) Robust and adaptive network flows. Oper. Res. 61(5):1218–1242.LinkGoogle Scholar
  • [12] Cormican KJ, Morton DP, Wood RK (1998) Stochastic network interdiction. Oper. Res. 46(2):184–197.LinkGoogle Scholar
  • [13] Disser Y, Matuschke J (2020) The complexity of computing a robust flow. Oper. Res. Lett. 48(1):18–23.CrossrefGoogle Scholar
  • [14] Dwivedi A, Yu X (2013) A maximum-flow-based complex network approach for power system vulnerability analysis. IEEE Trans. Indust. Inform. 9(1):81–88.CrossrefGoogle Scholar
  • [15] Gilpin A, Hoda S, Peña J, Sandholm T (2007) Gradient-based algorithms for finding Nash equilibria in extensive form games. Deng X, Graham FC, eds. Internet and Network Economics (Springer, Berlin Heidelberg), 57–69.CrossrefGoogle Scholar
  • [16] Goldman AJ, Tucker AW (1957) Theory of linear programming. Kuhn HW, Tucker AW, eds. Linear Inequalities and Related Systems, Annals of Mathematic Studies, vol. 38 (Princeton University Press, Princeton, NJ), 53–98.CrossrefGoogle Scholar
  • [17] Gueye A, Marbukh V (2012) A game-theoretic framework for network security vulnerability assessment and mitigation. Grossklags J, Walrand J, eds. Decision and Game Theory for Security (Springer, Berlin Heidelberg), 186–200.CrossrefGoogle Scholar
  • [18] Gueye A, Marbukh V, Walrand JC (2012) Towards a metric for communication network vulnerability to attacks: A game theoretic approach. Krishnamurthy V, Zhao Q, Huang M, Wen Y, eds. Game Theory for Networks (Springer, Berlin Heidelberg), 259–274.CrossrefGoogle Scholar
  • [19] Guo Q, An B, Zick Y, Miao C (2016) Optimal interdiction of illegal network flow. Proc. 25th Internat. Joint Conf. Artificial Intelligence (AAAI Press/IJCAI, Palo Alto, CA), 2507–2513.Google Scholar
  • [20] Hoàng CT (1994) Efficient algorithms for minimum weighted colouring of some classes of perfect graphs. Discrete Appl. Math. 55(2):133–143.CrossrefGoogle Scholar
  • [21] Jansen B, Roos C, Terlaky T (1994) The theory of linear programming: Skew symmetric self-dual problems and the central path. Optim. 29(3):225–233.CrossrefGoogle Scholar
  • [22] Karmarkar N (1984) A new polynomial-time algorithm for linear programming. Combinatorica 4(4):373–395.CrossrefGoogle Scholar
  • [23] Lipton RJ, Markakis E, Mehta A (2003) Playing large games using simple strategies. Proc. 4th ACM Conf. Electronic Commerce (ACM, New York), 36–41.Google Scholar
  • [24] McMahan HB, Gordon GJ, Blum A (2003) Planning in the presence of cost functions controlled by an adversary. Proc. 20th Internat. Conf. Machine Learn. (AAAI Press, Palo Alto, CA), 536–543.Google Scholar
  • [25] McMasters AW, Mustin TM (1970) Optimal interdiction of a supply network. Naval Res. Logist. Quart. 17(3):261–268.CrossrefGoogle Scholar
  • [26] Neumayer S, Zussman G, Cohen R, Modiano E (2008) Assessing the impact of geographically correlated network failures. Proc. 2008 Military Commun. Conf. (IEEE, Piscataway, NJ), 1–6.Google Scholar
  • [27] Orlin JB, Plotkin SA, Tardos É (1993) Polynomial dual network simplex algorithms. Math. Programming 60(1):255–276.CrossrefGoogle Scholar
  • [28] Ratliff HD, Sicilia GT, Lubore SH (1975) Finding the n most vital links in flow networks. Management Sci. 21(5):531–539.LinkGoogle Scholar
  • [29] Sullivan KM, Cole Smith J (2014) Exact algorithms for solving a Euclidean maximum flow network interdiction problem. Networks 64(2):109–124.CrossrefGoogle Scholar
  • [30] Szeto W (2013) Routing and scheduling hazardous material shipments: Nash game approach. Transportmetrica B: Transport Dynam. 1(3):237–260.CrossrefGoogle Scholar
  • [31] Washburn A, Wood K (1995) Two-person zero-sum games for network interdiction. Oper. Res. 43(2):243–251.LinkGoogle Scholar
  • [32] Wollmer R (1964) Removing arcs from a network. Oper. Res. 12(6):934–940.LinkGoogle Scholar
  • [33] Wood RK (1993) Deterministic network interdiction. Math. Comput. Model. 17(2):1–18.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.