An Entropy Function Implementation of Quadratic Programming

Abstract:

This paper is intended to describe a new algorithm, which makes entropy function method with Lagrange function and Taylor formula for solving inseparable variables of quadratic programming. Quadratic programming problem are an important in the fields of nonlinear programming problem. Entropy function also called KS function. The nature and related certificate of KS function and its convergence have already been proved at home and abroad. The application of KS function nature for solving quadratic programming is a very good method, and it is one of the advantages of making more constraint programming problem become a single constraint programming problem, and the original problems are simplified. Electing three examples of separated variables for quadratic programming problems, that is cross terms of zero, and then contrasted with the new method. The algorithm resolves implementation of separated variables of quadratic programming. Our numerical experiments show the proposed algorithm is feasible.

• Periodical: Applied Mechanics and Materials (Volumes 226-228)
• Pages: 2227-2230
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.226-228.2227
• Online since: November 2012
• Authors: Xiao Guang Wang, Chun Juan Hou
• Keywords: Entropy Function, Quadratic Programming, Separated Variables, Taylor Formula

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