Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/4415
Title: Some aspects of mathematical programming in statistics
Researcher: Bhat, Khurshid Ahmad
Guide(s): Ahmed, Aquil
Keywords: Physical science
Material Science
Mathematical programming
Statistics
Upload Date: 28-Aug-2012
University: University of Kashmir
Completed Date: 2011
Abstract: The Almighty has created the Universe and things present in it with an order and proper positions and the creation looks unique and perfect. No one can even think much better or imagine to optimize these further. People newlineinspired by these optimum results started thinking about usage of optimization techniques for solving their real life problems. The concept of constraint optimization came into being after World War II and its use spread vastly in all fields. However, in this process, still lots of efforts are needed to uncover the mysteries and unanswered questions, one of the newlinequestions always remains live that whether there can be a single method that can solve all types of nonlinear programming problems like Simplex Method solves linear programming problems. In the present thesis, we have newlinetried to proceed in this direction and provided some contributions towards this area. The present thesis has been divided into five chapters, chapter wise summary is given below: Chapter-1 is an introductory one and provides genesis of the Mathematical Programming Problems and its use in Statistics. Relationship of mathematical programming with other statistical measures are also reviewed. Definitions and other pre-requisites are also presented in this chapter. The relevant literature on the topic has been surveyed. Chapter-2 deals with the two dimensional non-linear programming newlineproblems. We develop a method that can solve approximately all type of two dimensional nonlinear programming problems of certain class. The method has been illustrated with numerical examples. Chapter-3 is devoted to the study of n-dimensional non-linear newlineprogramming problems of certain types. We provide a new method based on regression analysis and statistical distributions. The method can solve n-dimensional non-linear programming problems making use of regression analysis/co-efficient of determination.
Pagination: 96p.
URI: http://hdl.handle.net/10603/4415
Appears in Departments:Faculty of Physical and Material Sciences

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01_title.pdfAttached File35.19 kBAdobe PDFView/Open
02_certificate & acknowledgement.pdf20.9 kBAdobe PDFView/Open
03_abstract.pdf17.32 kBAdobe PDFView/Open
04_research publications.pdf16.06 kBAdobe PDFView/Open
05_contents.pdf64.86 kBAdobe PDFView/Open
06_chapter 1.pdf493.44 kBAdobe PDFView/Open
07_chapter 2.pdf100.74 kBAdobe PDFView/Open
08_chapter 3.pdf473.93 kBAdobe PDFView/Open
09_chapter 4.pdf94.12 kBAdobe PDFView/Open
10_chapter 5.pdf86.98 kBAdobe PDFView/Open
11_bibliography.pdf108.81 kBAdobe PDFView/Open


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