Connectivity reliability in uncertain networks with stability analysis
2016 (English)In: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 57, 337-344 p.Article in journal (Refereed) Published
This paper treats the fundamental problems of reliability and stability analysis in uncertain networks. Here, we consider a collapsed, post-disaster, traffic network that is composed of nodes (centers) and arcs (links), where the uncertain operationality or reliability of links is evaluated by domain experts. To ensure the arrival of relief materials and rescue vehicles to the disaster areas in time, uncertainty theory, which neither requires any probability distribution nor fuzzy membership function, is employed to originally propose the problem of choosing the most reliable path (MRP). We then introduce the new problems of α-most reliable path (α-MRP), which aims to minimize the pessimistic risk value of a path under a given confidence level α, and very most reliable path (VMRP), where the objective is to maximize the confidence level of a path under a given threshold of pessimistic risk. Then, exploiting these concepts, we give the uncertainty distribution of the MRP in an uncertain traffic network. The objective of bothα-MRP and VMRP is to determine a path that comprises the least risky route for transportation from a designated source node to a designated sink node, but with different decision criteria. Furthermore, a methodology is proposed to tackle the stability analysis issue in the framework of uncertainty programming; specifically, we show how to compute the arcs’ tolerances. Finally, we provide illustrative examples that show how our approaches work in realistic situation.
Place, publisher, year, edition, pages
2016. Vol. 57, 337-344 p.
Traffic network, Uncertainty theory, Reliability, Chance-constrained, Stability analysis
Information Systems Probability Theory and Statistics
Research subject Mathematics
IdentifiersURN: urn:nbn:se:umu:diva-120209DOI: 10.1016/j.eswa.2016.03.040ISI: 000376052200025OAI: oai:DiVA.org:umu-120209DiVA: diva2:927169