AbstractIn this paper, a stochastic version of each of the maximum flow and the minimum cost flow problems for a directed single commodity network, where the flow of units along each arc of the network forms a homogeneous Poisson process, are formulated as two chance constrained optimization problems and are solved based on the classical labeling algorithm and the primal-dual algorithm, respectively
When designing or upgrading a communication network, operators are faced with a major issue, as unce...
In Chapter 1, we present a stochastic shortest path problem that we refer to as the Most Likely Path...
The paper presents a genetic algorithm to generate minimal cuts for a stochastic flow network with c...
AbstractIn this paper, a stochastic version of each of the maximum flow and the minimum cost flow pr...
Many engineered systems, such as energy and transportation infrastructures, are networks governed by...
The deterministic theory of graphs and networks is used successfully in cases where no random compon...
Abstract—Solving network flow problems is a fundamental component of traffic engineering and many co...
We are interested in single commodity stochastic network design problems under prob-abilistic constr...
We are interested in single commodity stochastic network design problems under probabilistic constra...
In many practical cases, the data available for the formulation of an optimization model are known o...
It is possible to simulate a lot of real decision-making and conflict situations by random weighted ...
AbstractThis paper discusses a stochastic-flow network from single-commodity case to multicommodity ...
A comprehensive study of static transportation network optimization problems with stochastic user eq...
International audienceIn this paper, we study an interpretation of the sample-based approach to chan...
This thesis considers the network capacity design problem with demand uncertainty using the stochast...
When designing or upgrading a communication network, operators are faced with a major issue, as unce...
In Chapter 1, we present a stochastic shortest path problem that we refer to as the Most Likely Path...
The paper presents a genetic algorithm to generate minimal cuts for a stochastic flow network with c...
AbstractIn this paper, a stochastic version of each of the maximum flow and the minimum cost flow pr...
Many engineered systems, such as energy and transportation infrastructures, are networks governed by...
The deterministic theory of graphs and networks is used successfully in cases where no random compon...
Abstract—Solving network flow problems is a fundamental component of traffic engineering and many co...
We are interested in single commodity stochastic network design problems under prob-abilistic constr...
We are interested in single commodity stochastic network design problems under probabilistic constra...
In many practical cases, the data available for the formulation of an optimization model are known o...
It is possible to simulate a lot of real decision-making and conflict situations by random weighted ...
AbstractThis paper discusses a stochastic-flow network from single-commodity case to multicommodity ...
A comprehensive study of static transportation network optimization problems with stochastic user eq...
International audienceIn this paper, we study an interpretation of the sample-based approach to chan...
This thesis considers the network capacity design problem with demand uncertainty using the stochast...
When designing or upgrading a communication network, operators are faced with a major issue, as unce...
In Chapter 1, we present a stochastic shortest path problem that we refer to as the Most Likely Path...
The paper presents a genetic algorithm to generate minimal cuts for a stochastic flow network with c...
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