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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

Shape optimization under uncertainty from a stochastic programming point of view

Held, Harald. January 1900 (has links)
Diss.: University of Duisburg-Essen, 2009. / Includes bibliographical references (p. [127]-134).

Stability, approximation, and decomposition in two- and multistage stochastic programming

Küchler, Christian. January 2009 (has links)
Diss.: Berlin, Humboldt-University, 2009. / Includes bibliographical references (p. 159-168).

Pairing inequalities and stochastic lot-sizing problems a study in integer programming /

Guan, Yongpei. January 2005 (has links)
Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2006u. / Nemhauser, George L., Committee Chair ; Ahmed, Shabbir, Committee Member ; Bartholdi, John J., Committee Member ; Takriti, Samer, Committee Member ; Gu, Zonghao, Committee Member.

Semidefinite programming under uncertainty

Zhu, Yuntao, January 2006 (has links) (PDF)
Thesis (Ph. D.)--Washington State University, August 2006. / Includes bibliographical references.

Stochastic Programming Approach to Hydraulic Fracture Design for the Lower Tertiary Gulf of Mexico

Podhoretz, Seth 16 December 2013 (has links)
In this work, we present methodologies for optimization of hydraulic fracturing design under uncertainty specifically with reference to the thick and anisotropic reservoirs in the Lower Tertiary Gulf of Mexico. In this analysis we apply a stochastic programming framework for optimization under uncertainty and apply a utility framework for risk analysis. For a vertical well, we developed a methodology for making the strategic decisions regarding number and dimensions of hydraulic fractures in a high-cost, high-risk offshore development. Uncertainty is associated with the characteristics of the reservoir, the economics of the fracturing cost, and the fracture height growth. The method developed is applicable to vertical wells with multiple, partially penetrating fractures in an anisotropic formation. The method applies the utility framework to account for financial risk. For a horizontal well, we developed a methodology for making the strategic decisions regarding lateral length, number and dimensions of transverse hydraulic fractures in a high-cost, high-risk offshore development, under uncertainty associated with the characteristics of the reservoir. The problem is formulated as a mixed-integer, nonlinear, stochastic program and solved by a tailored Branch and Bound algorithm. The method developed is applicable to partially penetrating horizontal wells with multiple, partially penetrating fractures in an anisotropic formation.

Monte Carlo methods for multi-stage stochastic programs

Chiralaksanakul, Anukal 28 August 2008 (has links)
Not available / text

Monte Carlo sampling-based methods in stochastic programming

Bayraksan, Güzin 28 August 2008 (has links)
Not available / text

Bilevel factor analysis models

Pietersen, Jacobus Johannes 20 December 2007 (has links)
The theory of ordinary factor analysis and its application by means of software packages do not make provision for data sampled from populations with hierarchical structures. Since data are often obtained from such populations - educational data for example ¬the lack of procedures to analyse data of this kind needs to be addressed. A review of the ordinary factor analysis model and maximum likelihood estimation of the parameters in exploratory and confirmatory models is provided, together with practical applications. Subsequently, the concept of hierarchically structured populations and their models, called multilevel models, are introduced. A general framework for the estimation of the unknown parameters in these models is presented. It contains two estimation procedures. The first is the marginal maximum likelihood method in which an iterative expected maximisation approach is used to obtain the maximum likelihood estimates. The second is the Fisher scoring method which also provides estimated standard errors for the maximum likelihood parameter estimates. For both methods, the theory is presented for unconstrained as well as for constrained estimation. A two-stage procedure - combining the mentioned procedures - is proposed for parameter estimation in practice. Multilevel factor analysis models are introduced next, and subsequently a particular two-level factor analysis model is presented. The general estimation theory that was presented earlier is applied to this model - in exploratory and confirmatory analysis. First, the marginal maximum likelihood method is used to obtain the equations for determining the parameter estimates. It is then shown how an iterative expected max¬imisation algorithm is used to obtain these estimates in unconstrained and constrained optimisation. This method is applied to real life data using a FORTRAN program. Secondly, equations are derived by means of the Fisher scoring method to obtain the maximum likelihood estimates of the parameters in the two-level factor analysis model for exploratory and confirmatory analysis. A FORTRAN program was written to apply this method in practice. Real life data are used to illustrate the method. Finally, flowing from this research, some areas for possible further research are pro¬posed. / Thesis (PhD (Applied Statistics))--University of Pretoria, 2007. / Statistics / unrestricted

Optimising and controlling execution costs of block trading

Treloar, Richard Eric January 2000 (has links)
No description available.

Investment models based on clustered scenario trees.

January 2006 (has links)
Wong Man Hong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 60-63). / Abstracts in English and Chinese. / Abstract --- p.i / Abstract in Chinese --- p.ii / Thesis Assessment Committee --- p.iii / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Our Work and Motivation --- p.1 / Chapter 1.2 --- Literature Review --- p.3 / Chapter 1.3 --- Thesis Structure --- p.5 / Chapter 2 --- Preliminary --- p.6 / Chapter 2.1 --- Calculus for Volume of Sphere --- p.6 / Chapter 2.2 --- Fractional Programming and Dinkelbach's Algorithm --- p.7 / Chapter 2.3 --- Nonlinear Programming and Interior Point Algorithm --- p.8 / Chapter 2.4 --- Second Order Cones and Conic Programming --- p.10 / Chapter 3 --- The Probability Model --- p.12 / Chapter 3.1 --- Derive the Chance Constraint --- p.12 / Chapter 3.2 --- Single Cluster Model --- p.18 / Chapter 3.3 --- Multi-clusters Model --- p.21 / Chapter 4 --- The Downside Risk Model --- p.24 / Chapter 4.1 --- Derive the Downside Risk Measure --- p.24 / Chapter 4.2 --- Calculate the First and Second Derivative of the Downside Risk --- p.27 / Chapter 4.3 --- Single Cluster Model and Numerical Algorithm --- p.29 / Chapter 4.4 --- Multi-clusters Model --- p.34 / Chapter 5 --- The Conditional Value-at-Risk Model --- p.37 / Chapter 5.1 --- Derive the Conditional Value at Risk --- p.37 / Chapter 5.2 --- Single Cluster Model and Numerical Algorithm --- p.41 / Chapter 5.3 --- Multi-clusters Model --- p.47 / Chapter 6 --- Numerical Results --- p.51 / Chapter 6.1 --- Data Set --- p.51 / Chapter 6.2 --- The Probability Model --- p.53 / Chapter 6.3 --- The Downside Risk Model --- p.53 / Chapter 6.4 --- The CVaR Model --- p.56 / Chapter 7 --- Conclusions --- p.58 / Bibliography --- p.60

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