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.