A large number of problems involve making decisions in an uncertain environment and,
hence, with unknown outcomes. Optimization models aimed at controlling the trade‐off …

To keep up with the continuous growth in demand, cloud providers spend millions of dollars
augmenting the capacity of their wide-area backbones and devote significant effort to …

We study the design of resilient single-commodity flow networks that can remain robust
against multiple concurrent edge failures. We model these failures as binary random …

Many decision-making problems in the context of transhipment and logistics, distribution
networks, airline planning and so on, can best be analyzed by the means of maximum-flow …

A crucial challenge in network theory is the study of the robustness of a network when facing
a sequence of failures. In this work, we propose a dynamical definition of network …

We propose an approach to constructing metrics of network resilience, where resilience is
understood as the network's amenability to restoring its optimal or near‐optimal operations …

In this article, we study a Stochastic Minimum Cost Flow (SMCF) problem under arc failure
uncertainty, where an arc flow solution may correspond to multiple path flow …

In this work, we consider a class of risk-averse maximum weighted subgraph problems (R-
MWSP). Namely, assuming that each vertex of the graph is associated with a stochastic …

Vulnerabilities of complex networks have become a trend topic in complex systems due to its
applications to real-world problems. Most real networks tend to be very fragile to sequential …

This paper presents an approach to shortest path minimization for graphs with random
weights of arcs. To deal with uncertainty we use the following risk measures: Probability of …