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Journal of Applied Sciences
  Year: 2011 | Volume: 11 | Issue: 23 | Page No.: 3807-3810
DOI: 10.3923/jas.2011.3807.3810
An Approximation Method for Solving Nonconvex Quadratic Programming Problems
Ali Ahmadian and Reza Afsharinafar

Abstract:
In this study, we propose an approximate solution for nonconvex Quadratic Programming Problem (QPP) in general form using the eigenvalues of the Hessian matrix. Here we don't consider any special conditions (such as positive definiteness or positive semi definiteness) for the Hessian matrix of the objective function. Using the eigenvalues of the hessian matrix and solving two optimization problems, we propose an interval containing the optimal solution of QPP. This method can be useful for complicated and large scale optimization problems and also for integer quadratic programming problems.
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How to cite this article:

Ali Ahmadian and Reza Afsharinafar, 2011. An Approximation Method for Solving Nonconvex Quadratic Programming Problems. Journal of Applied Sciences, 11: 3807-3810.

DOI: 10.3923/jas.2011.3807.3810

URL: https://scialert.net/abstract/?doi=jas.2011.3807.3810

 
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