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Assessing the multistate flow networks' reliability and some applications

Abstract

Multistate flow networks (MFN) provide a powerful framework for understanding and modeling complex systems with multiple states and transitions. MFNs are used to model a wide range of real-world problems in various fields, including epidemiology (disease progression modeling), engineering (reliability analysis), finance (credit risk modeling), business (customer behavior analysis), and more. The problem of reliability evaluation of MFNs is essential for ensuring the safety, availability, and efficiency of complex systems, making this problem increasingly attractive in recent decades. It identifies critical components and states within a network, allowing organizations to implement cost-effective maintenance and repair strategies. Reliable MFNs underpin the continuous operation of essential services and industries such as healthcare, finance, and telecommunications that rely on consistent network performance to provide uninterrupted services, thereby maintaining economic stability. Several researchers worldwide have been working in this field of research over the last decades. However, the investigation continues as the related problems are NP-hard. This project aims to introduce exact and approximation techniques and approaches for addressing the network reliability problems outlined in the proposal. It achieves this by employing graph theory and network flow properties as fundamental tools in problem-solving. In addition to its primary objectives, this research proposal seeks to leverage the findings derived from the project to enhance existing solutions for evaluating the reliability of real-world systems, including power transmission and distribution systems and communication networks. Furthermore, our novel methodologies will be implemented in high-level programming languages such as C and Java. These implementations will facilitate comparative analyses with existing approaches documented in the literature. Additionally, this work desires to lay the base for the development of potential simulators for evaluating the reliability of MFNs. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
YEH, WEI-CHANG; FORGHANI-ELAHABAD, MAJID. An Efficient Algorithm for Sorting and Duplicate Elimination by Using Logarithmic Prime Numbers. BIG DATA AND COGNITIVE COMPUTING, v. 8, n. 9, p. 15-pg., . (23/13667-5)
YEH, WEI-CHANG; FORGHANI-ELAHABAD, MAJID. An efficient parallel approach for binary-state network reliability problems. ANNALS OF OPERATIONS RESEARCH, v. N/A, p. 22-pg., . (23/13667-5)