Novel Binary-Addition Tree Algorithm (BAT) for Binary-State Network Reliability Problem
Not on the map. Why?
Abstract (arXiv)
Network structures and models have been widely adopted, e.g., for Internet of Things, wireless sensor networks, smart grids, transportation networks, communication networks, social networks, and computer grid systems. Network reliability is an effective and popular technique to estimate the probability that the network is still functioning. Networks composed of binary-state (e.g., working or failed) components (arcs and/or nodes) are called binary-state networks. The binary-state network is the fundamental type of network; thus, there is always a need for a more efficient algorithm to calculate the network reliability. Thus, a novel binary-addition tree (BAT) algorithm that employs binary addition for finding all the possible state vectors and the path-based layered-search algorithm for filtering out all the connected vectors is proposed for calculating the binary-state network reliability. According to the time complexity and numerical examples, the efficiency of the proposed BAT is higher than those of traditional algorithms for solving the binary-state network reliability problem.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Apr 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1; 2026: 1.
4 papers.
- 2022Application of Long Short-Term Memory Recurrent Neural Networks Based on the BAT-MCS for Binary-State Network Approximated Time-Dependent Reliability Problemscited by 0
- 2024Applying Incremental Learning in Binary-Addition-Tree Algorithm for Dynamic Binary-State Network Reliabilitycited by 0
- 2025Data-Driven Approximation of Binary-State Network Reliability Function: Algorithm Selection and Reliability Thresholds for Large-Scale Systemscited by 0
- 2026Reference-state System Reliability method for scalable uncertainty quantification of coherent systemscited by 0
- 2026Reference-state System Reliability method for scalable uncertainty quantification of coherent systems18 Apr 2026
- 2025Data-Driven Approximation of Binary-State Network Reliability Function: Algorithm Selection and Reliability Thresholds for Large-Scale Systems16 Mar 2025
- 2024Applying Incremental Learning in Binary-Addition-Tree Algorithm for Dynamic Binary-State Network Reliability24 Sep 2024
- 2022Application of Long Short-Term Memory Recurrent Neural Networks Based on the BAT-MCS for Binary-State Network Approximated Time-Dependent Reliability Problems16 Feb 2022