Interdependent Network Recovery Games

被引:27
|
作者
Smith, Andrew M. [1 ]
Gonzalez, Andres D. [2 ,3 ]
Duenas-Osorio, Leonardo [2 ]
D'Souza, Raissa M. [1 ,4 ,5 ]
机构
[1] Univ Calif Davis, Dept Comp Sci, Davis, CA 95616 USA
[2] Rice Univ, Dept Civil Engn & Environm Engn, Houston, TX USA
[3] Univ Andes, Sch Engn, Bogota, Colombia
[4] Univ Calif Davis, Dept Mech & Aerosp Engn, Davis, CA 95616 USA
[5] Santa Fe Inst, Santa Fe, NM 87501 USA
关键词
Game theory; infrastructure recovery; optimization; INFRASTRUCTURE SYSTEMS; DESIGN; PREPAREDNESS; RESTORATION; RESILIENCE; MANAGEMENT; IMPACTS; RISK;
D O I
10.1111/risa.12923
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Recovery of interdependent infrastructure networks in the presence of catastrophic failure is crucial to the economy and welfare of society. Recently, centralized methods have been developed to address optimal resource allocation in postdisaster recovery scenarios of interdependent infrastructure systems that minimize total cost. In real-world systems, however, multiple independent, possibly noncooperative, utility network controllers are responsible for making recovery decisions, resulting in suboptimal decentralized processes. With the goal of minimizing recovery cost, a best-case decentralized model allows controllers to develop a full recovery plan and negotiate until all parties are satisfied (an equilibrium is reached). Such a model is computationally intensive for planning and negotiating, and time is a crucial resource in postdisaster recovery scenarios. Furthermore, in this work, we prove this best-case decentralized negotiation process could continue indefinitely under certain conditions. Accounting for network controllers' urgency in repairing their system, we propose an ad hoc sequential game-theoretic model of interdependent infrastructure network recovery represented as a discrete time noncooperative game between network controllers that is guaranteed to converge to an equilibrium. We further reduce the computation time needed to find a solution by applying a best-response heuristic and prove bounds on epsilon-Nash equilibrium, where epsilon depends on problem inputs. We compare best-case and ad hoc models on an empirical interdependent infrastructure network in the presence of simulated earthquakes to demonstrate the extent of the tradeoff between optimality and computational efficiency. Our method provides a foundation for modeling sociotechnical systems in a way that mirrors restoration processes in practice.
引用
收藏
页码:134 / 152
页数:19
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