A project Submitted in partial fulfllment of the requirements of the degree of master of science in mathematics

dc.contributor.advisorMitiku, Semu (PhD)
dc.contributor.authorGizaw, Dejene
dc.date.accessioned2018-07-12T11:13:16Z
dc.date.accessioned2023-11-04T12:30:46Z
dc.date.available2018-07-12T11:13:16Z
dc.date.available2023-11-04T12:30:46Z
dc.date.issued2014-06
dc.description.abstractIn this project work a smooth parametric nonlinear optimization problems subject to equality and inequality constraints are considered. Emphasis is given on those conditions under which the optimal solutions are di_erentiable functions of parameters. In theory these conditions are related to regularity conditions and to second order su_cient conditions. The interest in conditions for solution di_erentiability originates in the real-time computation (approximation) of perturbed optimal solutions under parameter changes through _rst order Taylor expansions. We study the explicit formulae and methods for computing for the sensitivity derivatives of the solution vector and the associated multipliers with respect to parameters. We discuss post-optimal evaluations of sensitivity derivatives and their numerical implementation. The purpose of this work is to describe the application of sensitivity analysis to approximate perturbed solutions in view of optimality and admissibility by using Taylor expansion and extend the sensitivity theory to provide a complete map of the optimal solution in the space of varying parameters for the case of multi-parametric quadratic programming(mpQP). Keywords. Nonlinear Optimization, Parametric nonlinear programming, Parametric quadratic programmingen_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/8337
dc.language.isoenen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectNonlinear Optimizationen_US
dc.subjectParametric Nonlinear Programmingen_US
dc.subjectParametric Quadratic Programmingen_US
dc.titleA project Submitted in partial fulfllment of the requirements of the degree of master of science in mathematicsen_US
dc.typeThesisen_US

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