Displaying similar documents to “Bound-based decision rules in multistage stochastic programming”

Risk objectives in two-stage stochastic programming models

Jitka Dupačová (2008)

Kybernetika

Similarity:

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...

Multistage stochastic programs via autoregressive sequences and individual probability constraints

Vlasta Kaňková (2008)

Kybernetika

Similarity:

The paper deals with a special case of multistage stochastic programming problems. In particular, the paper deals with multistage stochastic programs in which a random element follows an autoregressive sequence and constraint sets correspond to the individual probability constraints. The aim is to investigate a stability (considered with respect to a probability measures space) and empirical estimates. To achieve new results the Wasserstein metric determined by ℒ 1 norm and results of...

A two-stage stochastic optimization model for a gas sale retailer

F. Maggioni, Maria Teresa Vespucci, E. Allevi, Marida Bertocchi, M. Innorta (2008)

Kybernetika

Similarity:

The paper deals with a new stochastic optimization model, named OMoGaS–SV (Optimization Modelling for Gas Seller–Stochastic Version), to assist companies dealing with gas retail commercialization. Stochasticity is due to the dependence of consumptions on temperature uncertainty. Due to nonlinearities present in the objective function, the model can be classified as an NLP mixed integer model, with the profit function depending on the number of contracts with the final consumers, the...

Stochastic goal programming wth recourse

Antonio Heras Martínez, Ana García Aguado (1998)

Revista de la Real Academia de Ciencias Exactas Físicas y Naturales

Similarity:

In this article we discuss several alternative formulations for Stochastic Goal Programming. Only one of these models, which is a particular case of the Stochastic Programs with Recourse, is also compatible with Bayesian Decision Theory. Moreover, it is posible to approximate its solutions by means of an iterative algorithm.