A comparative study of the methods of solving non-linear programming problem
DOI:
https://doi.org/10.3329/diujst.v4i1.4352Keywords:
Non-linear programming, objective function, convex-region, pivotal element, optimal solutionAbstract
The work present in this paper is based on a comparative study of the methods of solving Non-linear programming (NLP) problem. We know that Kuhn-Tucker condition method is an efficient method of solving Non-linear programming 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 this paper in following way. Fist we discuss about non-linear programming problems. In second step we discuss Kuhn- Tucker condition method of solving NLP problems. Finally we compare the solution obtained by Kuhn- Tucker condition method with other methods. For problem so consider we use MATLAB programming to graph the constraints for obtaining feasible region. Also we plot the objective functions for determining optimum points and compare the solution thus obtained with exact solutions.
Keywords: Non-linear programming, objective function ,convex-region, pivotal element, optimal solution.
DOI: 10.3329/diujst.v4i1.4352
Daffodil International University Journal of Science and Technology Vol.4(1) 2009 pp.28-34
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