Stochastic Programming Approach in Stratified Sampling Problems
(Sprache: Englisch)
This book is based on the application of Stochastic programming techniques in Stratified Sampling problems. Stochastic programming deals with a class of optimization models and algorithms in which some of the data may be considered as random. First chapter...
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This book is based on the application of Stochastic programming techniques in Stratified Sampling problems. Stochastic programming deals with a class of optimization models and algorithms in which some of the data may be considered as random. First chapter provides a brief historical sketch of mathematical programming, stochastic programming and its application to various fields including sampling are presented. Various methods namely E-model, modified E-model, Branch and Bound approach and chance constrained programming are used to solve Probabilistic objective function & constraint into an equivalent deterministic. Allocation problems arising in univariate sratified sampling have been considered in first four (II-V) chapters and multivariate case in the last chapter. The problems are solved by first deriving the deterministic equivalents and then by using a suitable convex programming algorithm or by using the Chance constrained technique. Allocation problem in two stage stratified sampling with random parameters in both objective and constraints is also discussed. A numerical example is presented in all chapters and the problems are solved by LINGO software.
Bibliographische Angaben
- Autor: Ziaul Hassan Bakhshi
- 2015, 140 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 3659810916
- ISBN-13: 9783659810916
Sprache:
Englisch
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