DSAINov 13, 2025

Discounted Cuts: A Stackelberg Approach to Network Disruption

arXiv:2511.10804v1h-index: 34
Originality Incremental advance
AI Analysis

This work addresses network security and optimization for real-world infrastructure, though it is incremental as it builds on the Most Vital Links problem.

The authors tackled the problem of network disruption in a Stackelberg game between an attacker and defender, introducing discounted cuts to model edge removal and flow rerouting, and achieved polynomial-time solvability for bounded-genus graphs.

We study a Stackelberg variant of the classical Most Vital Links problem, modeled as a one-round adversarial game between an attacker and a defender. The attacker strategically removes up to $k$ edges from a flow network to maximally disrupt flow between a source $s$ and a sink $t$, after which the defender optimally reroutes the remaining flow. To capture this attacker--defender interaction, we introduce a new mathematical model of discounted cuts, in which the cost of a cut is evaluated by excluding its $k$ most expensive edges. This model generalizes the Most Vital Links problem and uncovers novel algorithmic and complexity-theoretic properties. We develop a unified algorithmic framework for analyzing various forms of discounted cut problems, including minimizing or maximizing the cost of a cut under discount mechanisms that exclude either the $k$ most expensive or the $k$ cheapest edges. While most variants are NP-complete on general graphs, our main result establishes polynomial-time solvability for all discounted cut problems in our framework when the input is restricted to bounded-genus graphs, a relevant class that includes many real-world networks such as transportation and infrastructure networks. With this work, we aim to open collaborative bridges between artificial intelligence, algorithmic game theory, and operations research.

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