Usage of task and data parallelism for finding the lower boundary vectors in a stochastic-flow network
Author:
Funder
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Publisher
Elsevier BV
Subject
Industrial and Manufacturing Engineering,Safety, Risk, Reliability and Quality
Reference66 articles.
1. Reliability modeling of modular k-out-of-n systems with functional dependency: A case study of radar transmitter systems;Xiahou;Reliab Eng Syst Saf,2023
2. A multistate network approach for reliability evaluation of unmanned swarms by considering information exchange capacity;Xu;Reliab Eng Syst Saf,2022
3. An analytical model for reliability assessment of the rail system considering dependent failures (case study of Iranian railway);Nazarizadeh;Reliab Eng Syst Saf,2022
4. Computing the reliability of a multistate flow network with flow loss effect;Niu;IEEE Trans Reliab,2023
5. Solving real-size stochastic railway rapid transit network construction scheduling problems;Canca;Comput Oper Res,2022
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A parallel algorithm for reliability assessment of multi-state flow networks based on simultaneous finding of all multi-state minimal paths and performing state space decomposition;Reliability Engineering & System Safety;2024-11
2. Expected performance evaluation and optimization of a multi-distribution multi-state logistics network based on network reliability;Reliability Engineering & System Safety;2024-11
3. A reliability index to measure multi-state flow network considering capacity restoration level and maintenance cost;Reliability Engineering & System Safety;2024-10
4. An algorithm to generate all d-lower boundary points for a stochastic flow network using dynamic flow constraints;Reliability Engineering & System Safety;2024-09
5. A path-based simulation approach for multistate flow network reliability estimation without using boundary points;Reliability Engineering & System Safety;2024-09
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3