Road networks reliability estimations and optimizations: A Bi-directional bottom-up, top-down approach
In this paper, the authors present a novel three-stage reduction-based estimation and optimization heuristics to evaluate and improve large-scale road networks’ reliability efficiently. Some necessary rules and tools are developed, in the 1st stage, to translate a large-scale physical road network into a mathematical graph. Then, in the 2nd stage, a bottom-up reduction algorithm is formulated to estimate network reliability. Finally, in the 3rd stage, a top-down method is proposed to improve the road network reliability by employing mathematical optimization models. Hence, this is a bidirectional bottom-up top-down (BUTD) method that (1) is genuinely based on the mathematical theory of reliability, (2) is computationally efficient by avoiding NP-hardness, and (3) by relaxing the need to employ pseudo metrics of reliability, e.g., vulnerability, resilience, etc. from the complex network theory in analyzing the large-scale road networks. The approach is explained using an illustrative example and a case study.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/09518320
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Supplemental Notes:
- © 2022 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
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Authors:
- Monfared, M A S
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0000-0002-6265-6115
- Rezazadeh, Masoumeh
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0000-0001-5481-0218
- Alipour, Zohreh
- Publication Date: 2022-6
Language
- English
Media Info
- Media Type: Web
- Features: Figures; Maps; References; Tables;
- Pagination: 108427
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Serial:
- Reliability Engineering & System Safety
- Volume: 222
- Issue Number: 0
- Publisher: Elsevier
- ISSN: 0951-8320
- Serial URL: https://www.sciencedirect.com/journal/reliability-engineering-and-system-safety
Subject/Index Terms
- TRT Terms: Heuristic methods; Mathematical models; Networks; Optimization; Reliability; Roads
- Subject Areas: Highways; Planning and Forecasting;
Filing Info
- Accession Number: 01852202
- Record Type: Publication
- Files: TRIS
- Created Date: Jul 21 2022 11:32AM