Playing Stackelberg Security Games in ...
Type de document :
Pré-publication ou Document de travail
DOI :
Titre :
Playing Stackelberg Security Games in Perfect Formulations
Auteur(s) :
Bustamante, Pamela [Auteur]
Pontificia Universidad Católica de Chile [UC]
Bucarey, Victor [Auteur]
Universidad de O'Higgins [UOH]
Labbé, Martine [Auteur]
Université libre de Bruxelles [ULB]
Integrated Optimization with Complex Structure [INOCS]
Marianov, Vladimir [Auteur]
Pontificia Universidad Católica de Chile [UC]
Ordoñez, Fernando [Auteur]
Universidad de Chile = University of Chile [Santiago] [UCHILE]
Pontificia Universidad Católica de Chile [UC]
Bucarey, Victor [Auteur]
Universidad de O'Higgins [UOH]
Labbé, Martine [Auteur]
Université libre de Bruxelles [ULB]
Integrated Optimization with Complex Structure [INOCS]
Marianov, Vladimir [Auteur]
Pontificia Universidad Católica de Chile [UC]
Ordoñez, Fernando [Auteur]
Universidad de Chile = University of Chile [Santiago] [UCHILE]
Date de publication :
2023
Mot(s)-clé(s) en anglais :
OR in Defense Bilevel Optimization Polyhedral structure Stackelberg Games
OR in Defense
Bilevel Optimization
Polyhedral structure
Stackelberg Games
OR in Defense
Bilevel Optimization
Polyhedral structure
Stackelberg Games
Discipline(s) HAL :
Computer Science [cs]/Operations Research [math.OC]
Résumé en anglais : [en]
Protecting critical infrastructure from intentional damage requires foreseeing the strategies of possible attackers. The problem faced by the defender of such infrastructure can be formulated as a Stackelberg security game. ...
Lire la suite >Protecting critical infrastructure from intentional damage requires foreseeing the strategies of possible attackers. The problem faced by the defender of such infrastructure can be formulated as a Stackelberg security game. A defender must decide what specific targets to protect with limited resources, maximizing their expected utility (e.g., minimizing damage value) and considering that a second player (or players), called attacker, responds in the best possible way. Since Stackelberg security games are generally NP-Hard, the main challenge in finding optimal strategies in real applications is developing efficient methodologies for large instances. We propose a general methodology to find a Strong Stackelberg Equilibrium for Stackelberg security games whose set of defender's mixed strategies can be represented as a perfect formulation. This methodology consists in two steps. First, we formulate the problem using variables representing the probabilities of each target being defended. The formulation must be either a polynomial-size MILP and/or a MILP with an exponential size of constraints that can be efficiently separated through branch-and-cut. In the second step, we recover the mixed strategies in the original space efficiently (in polynomial time) using column generation. This methodology has been applied in various security applications studied in the last decade. We generalize and propose new examples. Finally, we provide extensive computational study of different formulations based on marginal probabilities.Lire moins >
Lire la suite >Protecting critical infrastructure from intentional damage requires foreseeing the strategies of possible attackers. The problem faced by the defender of such infrastructure can be formulated as a Stackelberg security game. A defender must decide what specific targets to protect with limited resources, maximizing their expected utility (e.g., minimizing damage value) and considering that a second player (or players), called attacker, responds in the best possible way. Since Stackelberg security games are generally NP-Hard, the main challenge in finding optimal strategies in real applications is developing efficient methodologies for large instances. We propose a general methodology to find a Strong Stackelberg Equilibrium for Stackelberg security games whose set of defender's mixed strategies can be represented as a perfect formulation. This methodology consists in two steps. First, we formulate the problem using variables representing the probabilities of each target being defended. The formulation must be either a polynomial-size MILP and/or a MILP with an exponential size of constraints that can be efficiently separated through branch-and-cut. In the second step, we recover the mixed strategies in the original space efficiently (in polynomial time) using column generation. This methodology has been applied in various security applications studied in the last decade. We generalize and propose new examples. Finally, we provide extensive computational study of different formulations based on marginal probabilities.Lire moins >
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Anglais
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