MaxSAT Evaluation 2020 -- Benchmark: Identifying Maximum Probability Minimal Cut Sets in Fault Trees
Cryptography and Security
2020-07-17 v1 Discrete Mathematics
Logic in Computer Science
Networking and Internet Architecture
Systems and Control
Systems and Control
Abstract
This paper presents a MaxSAT benchmark focused on the identification of Maximum Probability Minimal Cut Sets (MPMCSs) in fault trees. We address the MPMCS problem by transforming the input fault tree into a weighted logical formula that is then used to build and solve a Weighted Partial MaxSAT problem. The benchmark includes 80 cases with fault trees of different size and composition as well as the optimal cost and solution for each case.
Cite
@article{arxiv.2007.08255,
title = {MaxSAT Evaluation 2020 -- Benchmark: Identifying Maximum Probability Minimal Cut Sets in Fault Trees},
author = {Martín Barrère and Chris Hankin},
journal= {arXiv preprint arXiv:2007.08255},
year = {2020}
}
Comments
5 pages, 1 figure. To appear in Proceedings of the MaxSAT Evaluation 2020 (MSE'20). https://maxsat-evaluations.github.io/2020/