Open AccessUsing "Filter" Approach to Solve the Constrained Optimization Problems
Author(s) -
Ban Ahmed Mitras
Publication year - 2010
Publication title -
maǧallaẗ al-rāfidayn li-ʿulūm al-ḥāsibāt wa-al-riyāḍiyyāẗ/al-rafidain journal for computer sciences and mathematics
Language(s) - English
Resource type - Journals
eISSN - 2311-7990
pISSN - 1815-4816
DOI - 10.33899/csmj.2010.163849
Subject(s) - sequential quadratic programming , penalty method , mathematical optimization , interior point method , nonlinear programming , point (geometry) , constraint (computer aided design) , convergence (economics) , constrained optimization , filter (signal processing) , quadratic programming , function (biology) , mathematics , constrained optimization problem , trust region , optimization problem , computer science , nonlinear system , economic growth , radius , economics , quantum mechanics , geometry , physics , computer security , computer vision , biology , evolutionary biology
In this paper, the solution of constrained nonlinear programming problems by a Sequential Quadratic Programming (SQP) is considered. The aim of the present work is to promote global convergence without the need to use a penalty and Barrier functions in the mixed interior-exterior point method. Instead, a new concept of a "filter" that aims to minimize the objective function and its approach that allows appoint to be accepted if reduces the objective function and satisfies the constraint violation function. If that point is rejected a new point is tested. Numerical tests on a wide range of test problems are very encouraging.
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