Résolution de problèmes d'optimisation dynamique par programmation dynamique marginaliste
Risk objectives in two-stage stochastic programming models
In applications of stochastic programming, optimization of the expected outcome need not be an acceptable goal. This has been the reason for recent proposals aiming at construction and optimization of more complicated nonlinear risk objectives. We will survey various approaches to risk quantification and optimization mainly in the framework of static and two-stage stochastic programs and comment on their properties. It turns out that polyhedral risk functionals introduced in Eichorn and Römisch...
Routage des voiliers et programmation dynamique
Self-tuning regulators with restricted inputs
Sequential importance sampling algorithms for dynamic stochastic programming.
Solvability and algorithms for functional equations originating from dynamic programming.
Solving multi-agent scheduling problems on parallel machines with a global objective function
In this study, we consider a scheduling environment with m(m ≥ 1) parallel machines. The set of jobs to schedule is divided into K disjoint subsets. Each subset of jobs is associated with one agent. The K agents compete to perform their jobs on common resources. The objective is to find a schedule that minimizes a global objective function f0, while maintaining the regular objective function of each agent, fk, at a level no greater than a fixed value, εk (fk ∈ {fkmax, ∑fk}, k = 0, ..., K). This...
Some ideas for comparison of Bellman chains
In this paper we are exploiting some similarities between Markov and Bellman processes and we introduce the main concepts of the paper: comparison of performance measures, and monotonicity of Bellman chains. These concepts are used to establish the main result of this paper dealing with comparison of Bellman chains.
Stochastic dynamic programming applied to hydrothermal power systems operation planning based on the convex hull algorithm.
Stochastic dynamic programming with random disturbances
Several peculiarities of stochastic dynamic programming problems where random vectors are observed before the decision ismade at each stage are discussed in the first part of this paper. Surrogate problems are given for such problems with distance properties (for instance, transportation problems) in the second part.
Su un particolare problema di allocazione di servizi
Subgraph isomorphism in planar graphs and related problems.
The Bellman equation related to the minimal entropy martingale measure.
The corridor method: a dynamic programming inspired metaheuristic
The expected discounted reward from a Markov replacement process
Three different operations research models for the same policy.
Time Petri nets state space reduction using dynamic programming
Un modèle de remplacement adaptatif
Une amélioration de l'algorithme récursif de Herz pour le problème de découpe à deux dimensions
Uniform value in dynamic programming
We consider dynamic programming problems with a large time horizon, and give sufficient conditions for the existence of the uniform value. As a consequence, we obtain an existence result when the state space is precompact, payoffs are uniformly continuous and the transition correspondence is non expansive. In the same spirit, we give an existence result for the limit value. We also apply our results to Markov decision processes and obtain a few generalizations of existing results.