This paper deals with robust optimization and network flows. Several robust variants of integer flow problems are considered. They assume uncertainty of network arc capacities as well as of arc unit costs (where applicable). Uncertainty is expressed by discrete scenarios. Since the considered variants of the maximum flow problem are easy to solve, the paper is mostly concerned with NP-hard variants of the minimum-cost flow problem, thus proposing an approximate algorithm for their solution. The accuracy of the proposed algorithm is verified by experiments
Stochastic network design is fundamental to transportation and logistic problems in practice, yet fa...
AbstractIn this paper, a stochastic version of each of the maximum flow and the minimum cost flow pr...
In a multiperiod dynamic network flow problem, we model uncertain arc capacities using scenario aggr...
The maximum flow problem is an optimization problem that aims to find the maximum flow value on a ne...
Solution robustness focuses on structural similarities between the nominal solution and the scenario...
This paper considers minimum cost flow problem in dynamic networks with uncertain costs. First, we p...
In this thesis, a maximum flow-based network interdiction problem considering uncertainties in arc c...
This thesis deals with optimization problems with uncertain data. Uncertainty here means that the da...
AbstractMinimum cost network design/dimensioning problems where feasibility has to be ensured w.r.t....
The Maximum Robust Flow problem asks for a flow on the paths of a network maximizing the guaranteed ...
We consider a robust network design problem: optimum in- tegral capacities need to be installed in a...
This thesis considers the network capacity design problem with demand uncertainty using the stochast...
We study a single-commodity Robust Network Design problem (sRND) defined on an undirected graph. Our...
International audienceWe propose a two-stage recoverable robustness approach that minimizes the reco...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Resea...
Stochastic network design is fundamental to transportation and logistic problems in practice, yet fa...
AbstractIn this paper, a stochastic version of each of the maximum flow and the minimum cost flow pr...
In a multiperiod dynamic network flow problem, we model uncertain arc capacities using scenario aggr...
The maximum flow problem is an optimization problem that aims to find the maximum flow value on a ne...
Solution robustness focuses on structural similarities between the nominal solution and the scenario...
This paper considers minimum cost flow problem in dynamic networks with uncertain costs. First, we p...
In this thesis, a maximum flow-based network interdiction problem considering uncertainties in arc c...
This thesis deals with optimization problems with uncertain data. Uncertainty here means that the da...
AbstractMinimum cost network design/dimensioning problems where feasibility has to be ensured w.r.t....
The Maximum Robust Flow problem asks for a flow on the paths of a network maximizing the guaranteed ...
We consider a robust network design problem: optimum in- tegral capacities need to be installed in a...
This thesis considers the network capacity design problem with demand uncertainty using the stochast...
We study a single-commodity Robust Network Design problem (sRND) defined on an undirected graph. Our...
International audienceWe propose a two-stage recoverable robustness approach that minimizes the reco...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Resea...
Stochastic network design is fundamental to transportation and logistic problems in practice, yet fa...
AbstractIn this paper, a stochastic version of each of the maximum flow and the minimum cost flow pr...
In a multiperiod dynamic network flow problem, we model uncertain arc capacities using scenario aggr...