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Minimizing Complementary Pivots in a Simplex-Based Solution Method for a Quadratic Programming Problem

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Author(s): Elias Munapo

Journal: American Journal of Operations Research
ISSN 2160-8830

Volume: 02;
Issue: 03;
Start page: 308;
Date: 2012;
Original page

Keywords: Quadratic Programming | Convex | Karusha-Kuhn-Tucker | Simplex Method

ABSTRACT
The paper presents an approach for avoiding and minimizing the complementary pivots in a simplex based solution method for a quadratic programming problem. The linearization of the problem is slightly changed so that the simplex or interior point methods can solve with full speed. This is a big advantage as a complementary pivot algorithm will take roughly eight times as longer time to solve a quadratic program than the full speed simplex-method solving a linear problem of the same size. The strategy of the approach is in the assumption that the solution of the quadratic programming problem is near the feasible point closest to the stationary point assuming no constraints.

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