Survivable network design under optimal and heuristic interdiction scenarios

Smith, J. Cole; Lim, Churlzu; Sudargho, Fransisca

doi:10.1007/s10898-006-9067-3

Cited by 76 publications

(32 citation statements)

References 27 publications

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“…Partial interdiction on arcs and interdiction budget to maximize the shortest path between supply and demand spots were considered by Fulkerson and Harding (1977) [15]. In the study of Smith et al (2007), partial interdiction was the reduction of the interdicted arcs' ow capacity [1]. Aksen et al (2012) integrated the partial interdiction idea into a facility interdiction model as a leader-follower game; the attacker had limited budget to cause interdiction, and the follower (defender) had to satisfy all customers' demand after attacking [4].…”

Section: Interdiction and Facility Forti Cation Modelsmentioning

confidence: 99%

“…Cr fṽ rg dr 0 Z 1 Cr fṽ rg dr: (22) We assume in this research thatṽ is a trapezoidal fuzzy number de ned by four constant points asṽ = (v (1) ; v (2) ; v (3) ; v (4) ). According to Expressions (23) and (24), the corresponding credibility measures and expected value ofṽ are computed as follows:…”

Section: The Proposed Credibility-based Fuzzy Chance Constrained Modelmentioning

confidence: 99%

“…In the context of intentional attacks, recent observations about world events show that facilities are vulnerable to terrorist attacks; thus, planning to relieve the impacts of facility interdictions can be an important issue for both private companies and public organizations. Several models are proposed for this situations [1][2][3]. By investigating the past terrorist attacks, we can conclude that terrorists applied unknown tactics and techniques to disrupt speci c targets; thus, determining these targets is more important for defenders than decoding attacker's techniques.…”

Section: Introductionmentioning

confidence: 99%

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Credibility-Based Fuzzy Mathematical Programming for Bi-Objective Capacitated Partial Facility Interdiction with Fortification and Demand Outsourcing Model

2017

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Abstract. The concepts of forti cation and partial interdiction have not been considered concurrently in previous studies. In this paper, we added the forti cation and partial interdiction concepts to interdiction problem for the rst time; the reason is that in interdiction situations, defenders decide to protect some important facilities according to their budgets, and attackers like to destroy most unprotected facilities according to their resources, and therefore, to cripple the defenders' systems. Moreover, we use the advantages of credibility-based fuzzy mathematical programming and introduce an integrated model based on uncertainty contexts. In this bi-objective model, decision-maker gives satisfaction degrees for constraints, and then we use the interactive possibility model to solve the bi-objective model with varying con dence levels. These con dence levels specify the knowledge of attacker and defender about themselves. In addition, we propose Genetic Algorithm (GA) to solve the suggested model. In the experiments, we generate problem instances and solve them by Multi-Objective Mixed-Integer Non-Linear Programming (MOMINLP) and the proposed genetic algorithm for various settings.

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Section: Interdiction and Facility Forti Cation Modelsmentioning

confidence: 99%

Section: The Proposed Credibility-based Fuzzy Chance Constrained Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Credibility-Based Fuzzy Mathematical Programming for Bi-Objective Capacitated Partial Facility Interdiction with Fortification and Demand Outsourcing Model

2017

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“…Kodialam and Lakshman [29] developed a sampling method for inspecting data packets to detect the intrusion of a computer virus or other illegal software. Smith et al [46] discussed the fortification of a telecommunication network against malicious attacks.…”

Section: Introductionmentioning

confidence: 99%

Effects of a Player's Awareness of Information Acquisition and Ability to Change Strategy in Attrition Games

Hohzaki

Tanaka

2017

JORSJ

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This paper deals with a two-person zero-sum (TPZS) attrition game on a network in which attackers depart from a start node and attempt to reach a destination node while defenders deploy to intercept the attackers. Both players incur some attrition due to conflict between them, but the payoff of the game is the number of surviving attackers reaching the destination. We generate a system of models categorized according to various scenarios of the player's information acquisition (IA) about his opponent and derive linear programming formulations for the equilibria of the models. Comparing the equilibria, we evaluate the values of the situations around the IA in a comprehensive manner.

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“…Scaparra and Church (2008) study the problem of allocating protective resources among the facilities of a system. Smith et al (2007) examine the problem of fortifying a network to defend against attacks in the context of survivable network design (e.g., Alevras et al, 1998;Myung et al, 1999;Ouveysi and Wirth, 1999). Desai and Sen (2010) consider the problem of designing reliable networks that satisfy several constraints while simultaneously allocating multiple resources to mitigate the arc failure probabilities such that the total cost of network design and resource allocation is minimized.…”

Section: Introductionmentioning

confidence: 99%

The multi-terminal maximum-flow network-interdiction problem

Akgün

Tansel

Wood

2011

European Journal of Operational Research

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a b s t r a c tThis paper defines and studies the multi-terminal maximum-flow network-interdiction problem (MTNIP) in which a network user attempts to maximize flow in a network among K P 3 pre-specified node groups while an interdictor uses limited resources to interdict network arcs to minimize this maximum flow. The paper proposes an exact (MTNIP-E) and an approximating model (MPNIM) to solve this NP-hard problem and presents computational results to compare the models. MTNIP-E is obtained by first formulating MTNIP as bi-level min-max program and then converting it into a mixed integer program where the flow is explicitly minimized. MPNIM is binary-integer program that does not minimize the flow directly. It partitions the node set into disjoint subsets such that each node group is in a different subset and minimizes the sum of the arc capacities crossing between different subsets. Computational results show that MPNIM can solve all instances in a few seconds while MTNIP-E cannot solve about one third of the problems in 24 hour. The optimal objective function values of both models are equal to each other for some problems while they differ from each other as much as 46.2% in the worst case. However, when the postinterdiction flow capacity incurred by the solution of MPNIM is computed and compared to the objective value of MTNIP-E, the largest difference is only 7.90% implying that MPNIM may be a very good approximation to MTNIP-E.

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Survivable network design under optimal and heuristic interdiction scenarios

Cited by 76 publications

References 27 publications

Credibility-Based Fuzzy Mathematical Programming for Bi-Objective Capacitated Partial Facility Interdiction with Fortification and Demand Outsourcing Model

Credibility-Based Fuzzy Mathematical Programming for Bi-Objective Capacitated Partial Facility Interdiction with Fortification and Demand Outsourcing Model

Effects of a Player's Awareness of Information Acquisition and Ability to Change Strategy in Attrition Games

The multi-terminal maximum-flow network-interdiction problem

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