Non linear programming comparative theory di bimal (3 risultati)
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Non-linear Programming Comparative theory and Examples | Comparative Study about the methods of Non-linear Programming Problem Including Different types of Numerical Examples | Bimal Das | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639263985 | Verantwortliche Person für die EU: VDM Ver…lag Dr. Müller, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Kartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Das BimalBimal Chandra Das is a faculty member of the Department of Textile Engineering, Daffodil International University, Dhaka, Bangladesh. He obtained his M.Sc Degree in Pu…re Mathematics from Chittagong University of Bangladesh i.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The work presented in this book is based on Comparative Study of the Methods of Solving Non-linear Programming (NLP) Problem Including Different types of Numerical Examples . We know that Kuhn-Tucker conditions method is an efficient me…thod of solving Non-linear programming (NLP) problem. By using Kuhn-Tucker conditions the quadratic programming (QP) problem reduced to form of Linear programming (LP) problem, so practically simplex type algorithm can be used to solve the quadratic programming problem (Wolfe's Algorithm). We have arranged the materials of the thesis in following way:In chapter-1 we discuss graphical solution method for solving all kinds of NLP problem. In chapter-2 we discuss other methods of solving NLP problem with numerical examples. In chapter-3 we compare the solutions of the problems obtained by graphical solution method with other methods. For all the problems so considered we use MATLAB programming to graph of the constraints for obtaining feasible regions. Also we plot the objective functions for determining optimum points and compare the solution thus obtained with exact solutions.
