12
IRUS Total
Downloads

MaxSAT Evaluation 2020 - Benchmark: Identifying maximum probability minimal cut sets in fault trees

File Description SizeFormat 
Benchmark-MSE20--Barrere-Hankin.pdfAccepted version281.27 kBAdobe PDFView/Open
Title: MaxSAT Evaluation 2020 - Benchmark: Identifying maximum probability minimal cut sets in fault trees
Authors: Barrere Cambrun, M
Hankin, C
Item Type: Conference Paper
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.
Editors: Bacchus, F
Berg, J
Järvisalo, M
Martins, R
Issue Date: 20-Aug-2020
Date of Acceptance: 3-Jul-2020
URI: http://hdl.handle.net/10044/1/81316
Publisher: University of Helsinki, Department of Computer Science
Journal / Book Title: MaxSAT Evaluation 2020: Solver and Benchmark Descriptions
Copyright Statement: © 2020 The Author(s)
Sponsor/Funder: Horizon2020
Funder's Grant Number: Project ID: 739551
Conference Name: MaxSAT Evaluation 2020 (affiliated with SAT 2020)
Keywords: MaxSAT
Benchmark
Fault Trees
Fault Tree Analysis
Reliability
Cyber-Physical Security
Dependability
cs.CR
cs.CR
cs.DM
cs.LO
cs.NI
cs.SY
eess.SY
68M15, 05C05, 94C15, 68R10, 90B25, 93B20, 90C27, 90C35, 68U07, 03B05
B.8; C.4; G.2.2; F.4.1; J.6; J.7; B.6.3; D.4.5; D.4.6; J.2
Publication Status: Published
Start Date: 2020-07-03
Finish Date: 2020-07-10
Conference Place: Alghero, Italy (Virtual in 2020)
Online Publication Date: 2020-08-20
Appears in Collections:Computing
Faculty of Engineering