Relevant bibliographies by topics / Interdiction networks

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Interdiction networks'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Interdiction networks"

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Gutin, Eli, Daniel Kuhn, and Wolfram Wiesemann. "Interdiction Games on Markovian PERT Networks." Management Science 61, no. 5 (2015): 999–1017. http://dx.doi.org/10.1287/mnsc.2014.1973.

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Wei, Xiangyu, Kai Xu, Peng Jiao, Quanjun Yin, and Yabing Zha. "A Decomposition Approach for Stochastic Shortest-Path Network Interdiction with Goal Threshold." Symmetry 11, no. 2 (2019): 237. http://dx.doi.org/10.3390/sym11020237.

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Shortest-path network interdiction, where a defender strategically allocates interdiction resource on the arcs or nodes in a network and an attacker traverses the capacitated network along a shortest s-t path from a source to a terminus, is an important research problem with potential real-world impact. In this paper, based on game-theoretic methodologies, we consider a novel stochastic extension of the shortest-path network interdiction problem with goal threshold, abbreviated as SSPIT. The attacker attempts to minimize the length of the shortest path, while the defender attempts to force it to exceed a specific threshold with the least resource consumption. In our model, threshold constraint is introduced as a trade-off between utility maximization and resource consumption, and stochastic cases with some known probability p of successful interdiction are considered. Existing algorithms do not perform well when dealing with threshold and stochastic constraints. To address the NP-hard problem, SSPIT-D, a decomposition approach based on Benders decomposition, was adopted. To optimize the master problem and subproblem iteration, an efficient dual subgraph interdiction algorithm SSPIT-S and a local research based better-response algorithm SSPIT-DL were designed, adding to the SSPIT-D. Numerical experiments on networks of different sizes and attributes were used to illustrate and validate the decomposition approach. The results showed that the dual subgraph and better-response procedure can significantly improve the efficiency and scalability of the decomposition algorithm. In addition, the improved enhancement algorithms are less sensitive and robust to parameters. Furthermore, the application in a real-world road network demonstrates the scalability of our decomposition approach.
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Held, Harald, and David L. Woodruff. "Heuristics for Multi-Stage Interdiction of Stochastic Networks." Journal of Heuristics 11, no. 5-6 (2005): 483–500. http://dx.doi.org/10.1007/s10732-005-3122-y.

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Yaghlane, Asma Ben, M. Naceur Azaiez, and Mehdi Mrad. "System survivability in the context of interdiction networks." Reliability Engineering & System Safety 185 (May 2019): 362–71. http://dx.doi.org/10.1016/j.ress.2019.01.005.

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Kosanoglu, Fuat, and Vicki M. Bier. "Target-oriented utility for interdiction of transportation networks." Reliability Engineering & System Safety 197 (May 2020): 106793. http://dx.doi.org/10.1016/j.ress.2020.106793.

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Ahumada-Paras, Mareldi, Kaarthik Sundar, Russell Bent, and Anatoly Zlotnik. "N-k interdiction modeling for natural gas networks." Electric Power Systems Research 190 (January 2021): 106725. http://dx.doi.org/10.1016/j.epsr.2020.106725.

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Jabarzare, Ziba, Hossein Zolfagharinia, and Mehdi Najafi. "Dynamic interdiction networks with applications in illicit supply chains." Omega 96 (October 2020): 102069. http://dx.doi.org/10.1016/j.omega.2019.05.005.

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Cuffe, Paul. "A Comparison of Malicious Interdiction Strategies Against Electrical Networks." IEEE Journal on Emerging and Selected Topics in Circuits and Systems 7, no. 2 (2017): 205–17. http://dx.doi.org/10.1109/jetcas.2017.2704879.

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Jiang, Shouyong, Yong Wang, Marcus Kaiser, and Natalio Krasnogor. "NIHBA: a network interdiction approach for metabolic engineering design." Bioinformatics 36, no. 11 (2020): 3482–92. http://dx.doi.org/10.1093/bioinformatics/btaa163.

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Abstract Motivation Flux balance analysis (FBA) based bilevel optimization has been a great success in redesigning metabolic networks for biochemical overproduction. To date, many computational approaches have been developed to solve the resulting bilevel optimization problems. However, most of them are of limited use due to biased optimality principle, poor scalability with the size of metabolic networks, potential numeric issues or low quantity of design solutions in a single run. Results Here, we have employed a network interdiction model free of growth optimality assumptions, a special case of bilevel optimization, for computational strain design and have developed a hybrid Benders algorithm (HBA) that deals with complicating binary variables in the model, thereby achieving high efficiency without numeric issues in search of best design strategies. More importantly, HBA can list solutions that meet users’ production requirements during the search, making it possible to obtain numerous design strategies at a small runtime overhead (typically ∼1 h, e.g. studied in this article). Availability and implementation Source code implemented in the MATALAB Cobratoolbox is freely available at https://github.com/chang88ye/NIHBA. Contact math4neu@gmail.com or natalio.krasnogor@ncl.ac.uk Supplementary information Supplementary data are available at Bioinformatics online.
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Chestnut, Stephen R., and Rico Zenklusen. "Hardness and approximation for network flow interdiction." Networks 69, no. 4 (2017): 378–87. http://dx.doi.org/10.1002/net.21739.

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Dissertations / Theses on the topic "Interdiction networks"

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Tangeman, Darrin K. "Intelligence collection, targeting and interdiction of dark networks." Thesis, Monterey, California: Naval Postgraduate School, 2014. http://hdl.handle.net/10945/42736.

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Approved for public release; distribution is unlimited<br>To interdict dark networks and prevent terrorist attacks, security forces require consistent access to relevant intelligence and targeting data. Dark networks often react to a security force’s targeting pressure by obscuring their activities and becoming increasingly covert. Network adaptation to targeting pressure can frequently lead to intelligence gaps and lulls in targeting that may be both predictable and preventable if identified early. This study will examine the efficacy of the two prevailing modes of targeting and their impact on resilient dark networks. To achieve this goal, this thesis will conduct a multivariate path analysis using temporal, geospatial, and relational data of a select dark network as these two modes of intelligence collection and targeting are employed against the network over time. By achieving this goal, this thesis will generate policy recommendations for operationalizing the outcomes of this study in order to better formulate how the prevailing modes of targeting can more effectively be implemented to address adaptive terrorist threats.
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Uygun, Adnan. "Network interdiction by Lagrangian relaxation and branch-and-bound." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2002. http://library.nps.navy.mil/uhtbin/hyperion-image/02Jun%5FUygun.pdf.

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Lunday, Brian Joseph. "Resource Allocation on Networks: Nested Event Tree Optimization, Network Interdiction, and Game Theoretic Methods." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77323.

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This dissertation addresses five fundamental resource allocation problems on networks, all of which have applications to support Homeland Security or industry challenges. In the first application, we model and solve the strategic problem of minimizing the expected loss inflicted by a hostile terrorist organization. An appropriate allocation of certain capability-related, intent-related, vulnerability-related, and consequence-related resources is used to reduce the probabilities of success in the respective attack-related actions, and to ameliorate losses in case of a successful attack. Given the disparate nature of prioritizing capital and material investments by federal, state, local, and private agencies to combat terrorism, our model and accompanying solution procedure represent an innovative, comprehensive, and quantitative approach to coordinate resource allocations from various agencies across the breadth of domains that deal with preventing attacks and mitigating their consequences. Adopting a nested event tree optimization framework, we present a novel formulation for the problem as a specially structured nonconvex factorable program, and develop two branch-and-bound schemes based respectively on utilizing a convex nonlinear relaxation and a linear outer-approximation, both of which are proven to converge to a global optimal solution. We also investigate a fundamental special-case variant for each of these schemes, and design an alternative direct mixed-integer programming model representation for this scenario. Several range reduction, partitioning, and branching strategies are proposed, and extensive computational results are presented to study the efficacy of different compositions of these algorithmic ingredients, including comparisons with the commercial software BARON. The developed set of algorithmic implementation strategies and enhancements are shown to outperform BARON over a set of simulated test instances, where the best proposed methodology produces an average optimality gap of 0.35% (compared to 4.29% for BARON) and reduces the required computational effort by a factor of 33. A sensitivity analysis is also conducted to explore the effect of certain key model parameters, whereupon we demonstrate that the prescribed algorithm can attain significantly tighter optimality gaps with only a near-linear corresponding increase in computational effort. In addition to enabling effective comprehensive resource allocations, this research permits coordinating agencies to conduct quantitative what-if studies on the impact of alternative resourcing priorities. The second application is motivated by the author's experience with the U.S. Army during a tour in Iraq, during which combined operations involving U.S. Army, Iraqi Army, and Iraqi Police forces sought to interdict the transport of selected materials used for the manufacture of specialized types of Improvised Explosive Devices, as well as to interdict the distribution of assembled devices to operatives in the field. In this application, we model and solve the problem of minimizing the maximum flow through a network from a given source node to a terminus node, integrating different forms of superadditive synergy with respect to the effect of resources applied to the arcs in the network. Herein, the superadditive synergy reflects the additional effectiveness of forces conducting combined operations, vis-à-vis unilateral efforts. We examine linear, concave, and general nonconcave superadditive synergistic relationships between resources, and accordingly develop and test effective solution procedures for the underlying nonlinear programs. For the linear case, we formulate an alternative model representation via Fourier-Motzkin elimination that reduces average computational effort by over 40% on a set of randomly generated test instances. This test is followed by extensive analyses of instance parameters to determine their effect on the levels of synergy attained using different specified metrics. For the case of concave synergy relationships, which yields a convex program, we design an inner-linearization procedure that attains solutions on average within 3% of optimality with a reduction in computational effort by a factor of 18 in comparison with the commercial codes SBB and BARON for small- and medium-sized problems; and outperforms these softwares on large-sized problems, where both solvers failed to attain an optimal solution (and often failed to detect a feasible solution) within 1800 CPU seconds. Examining a general nonlinear synergy relationship, we develop solution methods based on outer-linearizations, inner-linearizations, and mixed-integer approximations, and compare these against the commercial software BARON. Considering increased granularities for the outer-linearization and mixed-integer approximations, as well as different implementation variants for both these approaches, we conduct extensive computational experiments to reveal that, whereas both these techniques perform comparably with respect to BARON on small-sized problems, they significantly improve upon the performance for medium- and large-sized problems. Our superlative procedure reduces the computational effort by a factor of 461 for the subset of test problems for which the commercial global optimization software BARON could identify a feasible solution, while also achieving solutions of objective value 0.20% better than BARON. The third application is likewise motivated by the author's military experience in Iraq, both from several instances involving coalition forces attempting to interdict the transport of a kidnapping victim by a sectarian militia as well as, from the opposite perspective, instances involving coalition forces transporting detainees between interment facilities. For this application, we examine the network interdiction problem of minimizing the maximum probability of evasion by an entity traversing a network from a given source to a designated terminus, while incorporating novel forms of superadditive synergy between resources applied to arcs in the network. Our formulations examine either linear or concave (nonlinear) synergy relationships. Conformant with military strategies that frequently involve a combination of overt and covert operations to achieve an operational objective, we also propose an alternative model for sequential overt and covert deployment of subsets of interdiction resources, and conduct theoretical as well as empirical comparative analyses between models for purely overt (with or without synergy) and composite overt-covert strategies to provide insights into absolute and relative threshold criteria for recommended resource utilization. In contrast to existing static models, in a fourth application, we present a novel dynamic network interdiction model that improves realism by accounting for interactions between an interdictor deploying resources on arcs in a digraph and an evader traversing the network from a designated source to a known terminus, wherein the agents may modify strategies in selected subsequent periods according to respective decision and implementation cycles. We further enhance the realism of our model by considering a multi-component objective function, wherein the interdictor seeks to minimize the maximum value of a regret function that consists of the evader's net flow from the source to the terminus; the interdictor's procurement, deployment, and redeployment costs; and penalties incurred by the evader for misperceptions as to the interdicted state of the network. For the resulting minimax model, we use duality to develop a reformulation that facilitates a direct solution procedure using the commercial software BARON, and examine certain related stability and convergence issues. We demonstrate cases for convergence to a stable equilibrium of strategies for problem structures having a unique solution to minimize the maximum evader flow, as well as convergence to a region of bounded oscillation for structures yielding alternative interdictor strategies that minimize the maximum evader flow. We also provide insights into the computational performance of BARON for these two problem structures, yielding useful guidelines for other research involving similar non-convex optimization problems. For the fifth application, we examine the problem of apportioning railcars to car manufacturers and railroads participating in a pooling agreement for shipping automobiles, given a dynamically determined total fleet size. This study is motivated by the existence of such a consortium of automobile manufacturers and railroads, for which the collaborative fleet sizing and efforts to equitably allocate railcars amongst the participants are currently orchestrated by the \textit{TTX Company} in Chicago, Illinois. In our study, we first demonstrate potential inequities in the industry standard resulting either from failing to address disconnected transportation network components separately, or from utilizing the current manufacturer allocation technique that is based on average nodal empty transit time estimates. We next propose and illustrate four alternative schemes to apportion railcars to manufacturers, respectively based on total transit time that accounts for queuing; two marginal cost-induced methods; and a Shapley value approach. We also provide a game-theoretic insight into the existing procedure for apportioning railcars to railroads, and develop an alternative railroad allocation scheme based on capital plus operating costs. Extensive computational results are presented for the ten combinations of current and proposed allocation techniques for automobile manufacturers and railroads, using realistic instances derived from representative data of the current business environment. We conclude with recommendations for adopting an appropriate apportionment methodology for implementation by the industry.<br>Ph. D.
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Stavroulakis, Georgios. "Rapidly deployable, self forming, wireless networks for maritime interdiction operations." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FStavroulakis.pdf.

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Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, September 2006.<br>Thesis Advisor(s): Alex Bordetsky. "September 2006." Includes bibliographical references (p. 79-81). Also available in print.
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Kontogiannis, Theofanis. "Ad-Hoc Sensor Networks for Maritime Interdiction Operations and Regional Security." Thesis, Monterey, California. Naval Postgraduate School, 2012. http://hdl.handle.net/10945/17389.

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Robust communications are key to the success of naval operations such as area surveillance, control, and interdiction. Communication and sensor networks allow the flow of data and critical information that is necessary for conducting an operation from both the tactical and strategic perspectives. In naval operations, the platforms are hardly stationary, as the networking infrastructure operates from a variety of platforms in motion on the sea, above the sea, and from space, in the case of satellite support. Sensor networks consist of nodes made up of small sensors that are able to monitor, process, and analyze phenomena over geographical regions of varying sizes and for significant periods. Some categories of these small, and sometimes low-cost, sensors are able to collect and transmit, or relay, sensor data about physical values (e.g., temperature, humidity, and sea state), or dynamic attributes of objects, such as speed, direction, and the existence of dangerous substances (e.g., radioactive materials and explosives). The objective of this thesis is to examine how unstructured sensor networks, known also as ad-hoc sensor networks, can effectively support maritime interdiction operations and regional security by providing reliable communications and flow of information.
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Carnal, David D. "An enhanced implementation of models for electric power grid interdiction." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Sep%5FCarnal.pdf.

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Skoglund, Ulf. "Network interdiction." Thesis, Försvarshögskolan, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:fhs:diva-1824.

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Network Interdiction-problem innehåller två mot varandra stående styrkor, en användare och en angripare, somär inbegripna i en krigsliknande konflikt. Användaren använder ett nätverk för att optimera en funktion, t.ex.att förflytta en underhållskonvoj så snabbt som möjligt, eller maximera mängden materiel som transporterasgenom nätverket. Det innebär att användaren vill använda den kortaste eller snabbaste vägen vid transporter,och han vill maximera flödet genom nätverket. Nätverket kan t.ex. vara ett vägnät, kraftförsörjningsnät eller ettdatornätverk. Angriparen försöker begränsa användarens möjlighet att optimera sin funktion. Angriparenssyftet är att maximera den kortaste/snabbaste vägen eller att minimera det maximala flödet genom nätverket.Angriparen uppnår detta genom att angripa bågar eller noder i nätverket och förstöra dem totalt eller reduceraderas kapacitet. Angriparens resurser är begränsade och det finns ett behov av att optimera användandet. Imånga fall är nätverket stort och många parametrar påverkar planeringen. Detta ger en komplexplaneringsförutsättning för angriparen. Genomförs planläggningen av Network Interdiction på traditionellt sätt,tvingas planeraren att använda sin intuition. Resultatet beror till stor del på planläggarens förmåga och tid tillförfogande. Om algoritmer kunde användas för att stödja planläggaren, skulle resursutnyttjandet och effektenav angreppen kunna optimeras. Uppsatsen undersöker om det är möjligt att använda Network Interdictionalgoritmervid planering av Network Interdiction.<br>Network interdiction problems involve two opposing forces, a user and anattacker, who are engaged in a warlike conflict. The user operates a network inorder to optimize a function such as moving a supply convoy through thenetwork as quickly as possible, or maximizing the amount of materieltransported through the network. This means that the user is trying to use theshortest or the fastest route to perform transports, and he is trying to maximizethe flow trough the network. The network could be a road net, an electric powergrid or a computer network system. The attacker attempts to limit the user’spossibility to optimize his function. The purpose is to maximize the shortest andfastest route or to minimize the maximum flow through the network. Theattacker obtains this by interdicting arcs or nodes, e.g. by attacking arcs or nodesin order to destroy them entirely or to reduce their capacity. The attacker’sresources are limited and there is a need to optimize the use of them. In manycases the network is big and numerous parameters influence the planning. Thismakes the conditions for planning complex and difficult for the attacker. If theplanning of network interdiction is performed in the traditional way, the planneris forced to use intuition. The result will depend on the planner’s capacity and thetime at his disposal. If algorithms could be used to support the planner, theresources and the effect of the attack would be optimized. This thesis examines ifit is possible to use network interdiction algorithms to plan network interdiction.<br>Avdelning: ALB - Slutet Mag 3 C-upps.Hylla: Upps. ChP T 01-03
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Steinrauf, Robert L. "Network interdiction models." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/27159.

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Zheng, Jiefu. "Stochastic network interdiction games." Thesis, Boston University, 2013. https://hdl.handle.net/2144/11094.

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Thesis (Ph.D.)--Boston University<br>Network interdiction problems consist of games between an attacker and an intelligent network, where the attacker seeks to degrade network operations while the network adapts its operations to counteract the effects of the attacker. This problem has received significant attention in recent years due to its relevance to military problems and network security. When the attacker's actions achieve uncertain effects, the resulting problems become stochastic network interdiction problems. In this thesis, we develop new algorithms for the solutions of different classes of stochastic network interdiction problems. We first focus on static network interdiction games where the attacker attacks the network once, which will change the network with certain probability. Then the network will maximize the flow from a given source to its destination. The attacker is seeking a strategy which minimizes the expected maximum flow after the attack. For this problem, we develop a new solution algorithm, based on parsimonious integration of branch and bound techniques with increasingly accurate lower bounds. Our method obtains solutions significantly faster than previous approaches in the literature. In the second part, we study a multi-stage interdiction problem where the attacker can attack the network multiple times, and observe the outcomes of its past attacks before selecting a current attack. For this dynamic interdiction game, we use a model-predictive approach based on a lower bound approximation. We develop a new set of performance bounds, which are integrated into a modified branch and bound procedure that extends the single stage approach to multiple stages. We show that our new algorithm is faster than other available methods with simulated experiments. In the last part, we study the nested information game between an intelligent network and an attacker, where the attacker has partial information about the network state, which refers to the availability of arcs. The attacker does not know the exact state, but has a probability distribution over the possible network states. The attacker makes several attempts to attack the network and observes the flows on the network. These observations will update the attacker's knowledge of the network and will be used in selecting the next attack actions. The defender can either send flow on that arc if it survived, or refrain from using it in order to deceive the attacker. For these problems, we develop a faster algorithm, which decomposes this game into a sequence of subgames and solves them to get the equilibrium strategy for the original game. Numerical results show that our method can handle large problems which other available methods fail to solve.
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Xiaodan, Xie. "Network Interdiction Model on Interdependent Incomplete Network." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1593537784177702.

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Books on the topic "Interdiction networks"

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Steinrauf, Robert L. Network interdiction models. Naval Postgraduate School, 1991.

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Woodruff, David L., ed. Network Interdiction and Stochastic Integer Programming. Kluwer Academic Publishers, 2003. http://dx.doi.org/10.1007/b101869.

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Derbes, H. Dan. Efficiently interdicting a time-expanded transshipment network. Naval Postgraduate School, 1997.

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United States. Congress. Senate. Committee on Governmental Affairs. Permanent Subcommittee on Investigations. Federal drug interdiction: Command, control, communications, and intelligence network : hearings before the Permanent Subcommittee on Investigations of the Committee on Governmental Affairs, United States Senate, One hundredth Congress, first session, March 18 and 24, 1987. U.S. G.P.O., 1987.

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L, Woodruff David, ed. Network interdiction and stochastic integer programming. Kluwer Academic Publishers, 2003.

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Woodruff, David L. Network Interdiction and Stochastic Integer Programming. Springer, 2013.

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Woodruff, David L. Network Interdiction and Stochastic Integer Programming (Operations Research/Computer Science Interfaces Series). Springer, 2002.

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Network Interdiction by Lagrandian Relaxation and Branch-and-Bound. Storming Media, 2002.

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Efficiently Interdicting a Time-Expanded Transshipment Network. Storming Media, 1997.

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Book chapters on the topic "Interdiction networks"

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Woo, Gordon. "Interdiction of Plots with Multiple Operatives." In Lecture Notes in Social Networks. Springer Vienna, 2011. http://dx.doi.org/10.1007/978-3-7091-0388-3_4.

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Wu, Keyu, Zhou Zhang, Xingchen Hu, Boliang Sun, and Chao Chen. "Vulnerability Analysis of Wireless Sensor Networks via Maximum Flow Interdiction." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44751-9_26.

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Washburn, Alan. "Network Interdiction." In International Series in Operations Research & Management Science. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-9050-0_7.

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Bahamondes, Bastián, José Correa, Jannik Matuschke, and Gianpaolo Oriolo. "Adaptivity in Network Interdiction." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68711-7_3.

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Smith, J. Cole, Mike Prince, and Joseph Geunes. "Modern Network Interdiction Problems and Algorithms." In Handbook of Combinatorial Optimization. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-7997-1_61.

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Smith, J. Cole, and Churlzu Lim. "Algorithms for Network Interdiction and Fortification Games." In Pareto Optimality, Game Theory And Equilibria. Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-77247-9_24.

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Karam, P. Andrew. "Developing a Radiological and Nuclear Interdiction Network." In Advanced Sciences and Technologies for Security Applications. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69162-2_13.

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Torres, Marina, Shouyong Jiang, David Pelta, Marcus Kaiser, and Natalio Krasnogor. "Strain Design as Multiobjective Network Interdiction Problem: A Preliminary Approach." In Advances in Artificial Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00374-6_26.

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Yates, Justin. "Network Interdiction Methods and Approximations in a Hazmat Transportation Setting." In International Series in Operations Research & Management Science. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6794-6_7.

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Schäfer, Luca E., Tobias Dietz, Marco V. Natale, Stefan Ruzika, Sven O. Krumke, and Carlos M. Fonseca. "The Bicriterion Maximum Flow Network Interdiction Problem in s-t-Planar Graphs." In Operations Research Proceedings. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48439-2_16.

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Conference papers on the topic "Interdiction networks"

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Zhang, Youzhi, Bo An, Long Tran-Thanh, Zhen Wang, Jiarui Gan, and Nicholas R. Jennings. "Optimal Escape Interdiction on Transportation Networks." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/550.

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Preventing crimes or terrorist attacks in urban areas is challenging. Law enforcement officers need to respond quickly to catch the attacker on his escape route, which is subject to time-dependent traffic conditions on transportation networks. The attacker can strategically choose his escape path and driving speed to avoid being captured. Existing work on security resource allocation has not considered such scenarios with time-dependent strategies for both players. Therefore, in this paper, we study the problem of efficiently scheduling security resources for interdicting the escaping attacker. We propose: 1) a new defender-attacker security game model for escape interdiction on transportation networks; and 2) an efficient double oracle algorithm to compute the optimal defender strategy, which combines mixed-integer linear programming formulations for best response problems and effective approximation algorithms for improving the scalability of the algorithms. Experimental evaluation shows that our approach significantly outperforms baselines in solution quality and scales up to realistic-sized transportation networks with hundreds of intersections.
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2

Zhang, Tianyun, and Makan Fardad. "On the Optimal Interdiction of Transportation Networks." In 2020 American Control Conference (ACC). IEEE, 2020. http://dx.doi.org/10.23919/acc45564.2020.9147435.

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3

Xiangyu, Wei, Xiao Kaiming, and Duan Wei. "Shortest path network interdiction of bi-layer networks with goal threshold." In 2016 13th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2016. http://dx.doi.org/10.1109/iccwamtip.2016.8079807.

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4

Bartolacci, Michael, Stanko Dimitrov, and Larry LeBlanc. "Promoting Resiliency in Emergency Communication Networks: A Network Interdiction Modeling Approach." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2017. http://dx.doi.org/10.24251/hicss.2017.303.

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5

Xiao, Kaiming, Cheng Zhu, Weiming Zhang, Xiangyu Wei, and Songchao Hu. "Stackelberg network interdiction game: nodal model and algorithm." In 2014 5th International Conference on Game Theory for Networks (GAMENETS). IEEE, 2014. http://dx.doi.org/10.1109/gamenets.2014.7043716.

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6

Kuhnle, Alan, Victoria G. Crawford, and My T. Thai. "Scalable and Adaptive Algorithms for the Triangle Interdiction Problem on Billion-Scale Networks." In 2017 IEEE International Conference on Data Mining (ICDM). IEEE, 2017. http://dx.doi.org/10.1109/icdm.2017.33.

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7

Hong, Sunghoon. "Strategic network interdiction." In the Behavioral and Quantitative Game Theory. ACM Press, 2010. http://dx.doi.org/10.1145/1807406.1807418.

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8

Jiefu Zheng and D. A. Castanon. "Stochastic dynamic network interdiction games." In 2012 American Control Conference - ACC 2012. IEEE, 2012. http://dx.doi.org/10.1109/acc.2012.6315444.

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9

Guo, Qingyu, Bo An, and Long Tran-Thanh. "Playing Repeated Network Interdiction Games with Semi-Bandit Feedback." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/515.

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Abstract:
We study repeated network interdiction games with no prior knowledge of the adversary and the environment, which can model many real world network security domains. Existing works often require plenty of available information for the defender and neglect the frequent interactions between both players, which are unrealistic and impractical, and thus, are not suitable for our settings. As such, we provide the first defender strategy, that enjoys nice theoretical and practical performance guarantees, by applying the adversarial online learning approach. In particular, we model the repeated network interdiction game with no prior knowledge as an online linear optimization problem, for which a novel and efficient online learning algorithm, SBGA, is proposed, which exploits the unique semi-bandit feedback in network security domains. We prove that SBGA achieves sublinear regret against adaptive adversary, compared with both the best fixed strategy in hindsight and a near optimal adaptive strategy. Extensive experiments also show that SBGA significantly outperforms existing approaches with fast convergence rate.
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10

Fu, Xinzhe, and Eytan Modiano. "Network Interdiction Using Adversarial Traffic Flows." In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications. IEEE, 2019. http://dx.doi.org/10.1109/infocom.2019.8737475.

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Reports on the topic "Interdiction networks"

1

Cormican, Kelly J., David P. Morton, and R. K. Wood. Stochastic Network Interdiction. Defense Technical Information Center, 1998. http://dx.doi.org/10.21236/ada491085.

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2

Washburn, Alan. Continuous Network Interdiction. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada449515.

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3

Chauhan, Darshan Rajesh. Robust Maximum Flow Network Interdiction Problem. Portland State University Library, 2020. http://dx.doi.org/10.15760/etd.7315.

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