Fast computation of bounds for two-terminal network reliability

Sebastio, Stefano; Trivedi, Kishor S.; Wang, Dazhi; Yin, Xi

doi:10.1016/j.ejor.2014.04.035

Cited by 44 publications

(27 citation statements)

References 63 publications

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“…A more recent approach [35] computes two-terminal reliability bounds using a BDD for representing the reliability graph. It starts by considering only disjoint mincuts and minpaths, and if the desired bound accuracy is not achieved then it proceeds to an exhaustive search of mincuts and minpaths.…”

Section: Background and Related Workmentioning

confidence: 99%

“…This algorithm builds on our earlier work [39], incorporating new heuristics that lead to significant improvement in the overall performance. Note that the proposed approach (as the algorithm in [35] for calculating two-terminal reliability bounds) does not need to enumerate all mincuts or minpaths and generally obtains bounds with the desired accuracy in a reasonable amount of time. It is important to stress that for networks with a large number of edges the number of mincuts is so large (2 N−1 − 1, for complete graphs with N vertices) that the time and memory needed to retrieve all the mincuts are infeasible and so exact calculation becomes impractical.…”

Section: Introductionmentioning

confidence: 99%

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An effective algorithm for computing all‐terminal reliability bounds

et al. 2015

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Section: Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An effective algorithm for computing all‐terminal reliability bounds

et al. 2015

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“…This approach is easy to implement; its performance, however, degrades for large networks because of the exponential growth of minimal tie/cut sets. Approach 2 (Approximation): Approximation methods were proposed to reduce execution time and computational complexity. These approaches use lower and upper bounds of reliability or sampling techniques (Monte Carlo Simulation methods) to estimate the results. Approach 3 (Binary decision diagram (BDD) technique): To overcome the weakness of the first approach, BDD‐based methods have been proposed by various authors . A BDD is considered as an efficient data structure for storing large numbers of Boolean terms …”

Section: Introductionmentioning

confidence: 99%

“…These approaches use lower and upper bounds of reliability [16][17][18] or sampling techniques (Monte Carlo Simulation methods [19][20][21] to estimate the results. • Approach 3 (Binary decision diagram (BDD) technique): To overcome the weakness of the first approach, BDD-based methods have been proposed by various authors.…”

Section: Introductionmentioning

confidence: 99%

A Parallel Strategy for the Logical‐probabilistic Calculus‐based Method to Calculate Two‐terminal Reliability

Nguyen

2015

Quality & Reliability Eng

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The theory of network reliability has been applied to many complicated network structures, such as computer and communication networks, piping systems, electricity networks, and traffic networks. The theory is used to evaluate the operational performance of networks that can be modeled by probabilistic graphs. Although evaluating network reliability is an Non-deterministic Polynomial-time hard problem, numerous solutions have been proposed. However, most of them are based on sequential computing, which under-utilizes the benefits of multi-core processor architectures. This paper addresses this limitation by proposing an efficient strategy for calculating the two-terminal (terminal-pair) reliability of a binary-state network that uses parallel computing. Existing methods are analyzed. Then, an efficient method for calculating terminal-pair reliability based on logical-probabilistic calculus is proposed. Finally, a parallel version of the proposed algorithm is developed. This is the first study to implement an algorithm for estimating terminal-pair reliability in parallel on multicore processor architectures. The experimental results show that the proposed algorithm and its parallel version outperform an existing sequential algorithm in terms of execution time.

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“…Every sequentially selected cutset and pathset is considered in this algorithm. A more effective algorithm is presented in [12] where, similarly to the approach in [21], the pathsets and cutsets that do not contribute significantly to reducing the reliability gap are ignored. Also in [12] the maximally disjoint pathsets are first considered, followed by the pathsets generated by decreasing probability.…”

Section: Iterative Pathset and Cutset Generationmentioning

confidence: 99%

A Comparison between Two All-Terminal Reliability Algorithms

Pino¹,

Gomes²,

Kooij³

2015

JACN

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Abstract-Two algorithms computing the all-terminal reliability are compared. The first algorithm uses the pathsets and cutsets of the network to find lower and upper bounds respectively. The second algorithm uses decomposition and is able to give an exact outcome. The latter approach is significantly faster and able to calculate the exact value. However, for some large networks the decomposition algorithm does not give results while the path-and cutset algorithm still returns bounds. The low computation times of the proposed decomposition algorithm make it feasible to incorporate the repeated calculation of the all-terminal reliability in new types of network analysis. Some illustrations of these analyses are provided. IndexTerms-All-terminal network reliability, decomposition, network availability, pathwidth.

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Fast computation of bounds for two-terminal network reliability

Cited by 44 publications

References 63 publications

An effective algorithm for computing all‐terminal reliability bounds

An effective algorithm for computing all‐terminal reliability bounds

A Parallel Strategy for the Logical‐probabilistic Calculus‐based Method to Calculate Two‐terminal Reliability

A Comparison between Two All-Terminal Reliability Algorithms

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