Stochastic Linear Programming Stochastic Linear Programming

Stochastic Linear Programming

Models, Theory, and Computation

    • 89,99 $
    • 89,99 $

Description de l’éditeur

Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. STOCHASTIC LINEAR PROGRAMMING: Models, Theory, and Computation is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature. The application area of stochastic programming includes portfolio analysis, financial optimization, energy problems, random yields in manufacturing, risk analysis, etc. In this book models in financial optimization and risk analysis are discussed as examples, including solution methods and their implementation.


Stochastic programming is a fast developing area of optimization and mathematical programming. Numerous papers and conference volumes, and several monographs have been published in the area; however, the Kall & Mayer book will be particularly useful in presenting solution methods including their solid theoretical basis and their computational issues, based in many cases on implementations by the authors. The book is also suitable for advanced courses in stochastic optimization.

GENRE
Science et nature
SORTIE
2006
30 mars
LANGUE
EN
Anglais
LONGUEUR
410
Pages
ÉDITEUR
Springer US
VENDEUR
Springer Nature B.V.
TAILLE
35,8
 Mo
Optimization and Control with Applications Optimization and Control with Applications
2006
Generalized Bounds for Convex Multistage Stochastic Programs Generalized Bounds for Convex Multistage Stochastic Programs
2006
Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett Computational Methods for Modeling of Nonlinear Systems by Anatoli Torokhti and Phil Howlett
2007
High-Dimensional Optimization and Probability High-Dimensional Optimization and Probability
2022
Monte Carlo and Quasi-Monte Carlo Methods 2006 Monte Carlo and Quasi-Monte Carlo Methods 2006
2007
Numerical Mathematics and Advanced Applications Numerical Mathematics and Advanced Applications
2008
Systems Modelling and Optimization Proceedings of the 18th IFIP TC7 Conference Systems Modelling and Optimization Proceedings of the 18th IFIP TC7 Conference
2022
Stochastic Linear Programming Stochastic Linear Programming
2010