Adversarial Training for Robust Coverage Network under Worst-case Facility Losses 事件

Adversarial Training for Robust Coverage Network under Worst-case Facility Losses arXiv:2605.26763v1 Announce Type: cross Abstract: The Maximal Covering Location-Interdiction Problem (MCLIP) is a classic bi-level optimization problem, which is fundamental to resilient infrastructure planning yet remains computationally intractable. Specifically, the upper level determines facility locations to maximize coverage, while the lower level executes worst-case interdiction to minimize the coverage. Th