Non-linear Programming Comparative theory and Examples

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 method 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.

Autorentext

Bimal Chandra Das obtained his M.Sc Degree in Pure Mathematics from Chittagong University of Bangladesh in 2001 and his B.Sc in Mathematics from the same University in 2000.Currently,he is working as a Senior Lecturer at the Department of Textile Engineering in Faculty of SIT,Daffodil International University,Bangladesh.

Klappentext

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 method 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.