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Consider the Quadratic Programming problem:
, 2004
"... Abstract. A quadratic programming problem with positive definite Hessian and bound constraints is solved, using a Lagrange multiplier approach. The proposed method falls in the category of exterior point, active set techniques. An iteration of our algorithm modifies both the minimization parameters ..."
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Abstract. A quadratic programming problem with positive definite Hessian and bound constraints is solved, using a Lagrange multiplier approach. The proposed method falls in the category of exterior point, active set techniques. An iteration of our algorithm modifies both the minimization parameters
A note on permutations for quadratic programming problems
, 2006
"... 1 A note on permutations for quadratic programming problems ..."
An Algorithm for Solving Quadratic Programming Problems
"... Herein is investigated the method of solution of quadratic programming problems. The algorithm is based on the effective selection of constraints. Quadratic programming with constraintsequalities are solved with the help of an algorithm, so that matrix inversion is avoided, because of the more conve ..."
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Cited by 1 (0 self)
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Herein is investigated the method of solution of quadratic programming problems. The algorithm is based on the effective selection of constraints. Quadratic programming with constraintsequalities are solved with the help of an algorithm, so that matrix inversion is avoided, because of the more
ON PARAMETRIC LINEAR AND QUADRATIC PROGRAMMING PROBLEMS
, 1981
"... An algorithm is described for determining the optimal solution of parametric linear and quadratic programming problems as an explicit piecewise linear function of the parameter. Each linear function is uniquely determined by an appropriate subset of active constraints. For every critical value of ..."
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An algorithm is described for determining the optimal solution of parametric linear and quadratic programming problems as an explicit piecewise linear function of the parameter. Each linear function is uniquely determined by an appropriate subset of active constraints. For every critical value
Heuristic Algorithms for the Unconstrained Binary Quadratic Programming Problem
, 1998
"... In this paper we consider the unconstrained binary quadratic programming problem. This is the problem of maximising a quadratic objective by suitable choice of binary (zeroone) variables. We present two heuristic algorithms based upon tabu search and simulated annealing for this problem. Computatio ..."
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Cited by 41 (0 self)
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In this paper we consider the unconstrained binary quadratic programming problem. This is the problem of maximising a quadratic objective by suitable choice of binary (zeroone) variables. We present two heuristic algorithms based upon tabu search and simulated annealing for this problem
Memetic Algorithms for the Unconstrained Binary Quadratic Programming Problem
 BioSystems
, 2004
"... This paper presents a memetic algorithm, a highly eective evolutionary algorithm incorporating local search for solving the unconstrained binary quadratic programming problem (BQP). To justify the approach, a tness landscape analysis is conducted experimentally for several instances of the BQP. ..."
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Cited by 21 (4 self)
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This paper presents a memetic algorithm, a highly eective evolutionary algorithm incorporating local search for solving the unconstrained binary quadratic programming problem (BQP). To justify the approach, a tness landscape analysis is conducted experimentally for several instances of the BQP
A New Heuristic for the Convex Quadratic Programming Problem
, 2015
"... This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual KarushKuhnTucker conditions are used but in this case a linear objective function is also formulated from the set of linear equations and complementarity slackness conditions. An unboundedness cha ..."
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This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual KarushKuhnTucker conditions are used but in this case a linear objective function is also formulated from the set of linear equations and complementarity slackness conditions. An un
Consider the following convex quadratic programming problem
, 2013
"... Copyright © 2014 Ruopeng Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accordance of the Creative Commons Attributi ..."
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Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property Ruopeng Wang et al. All Copyright © 2014 are guarded by law and by SCIRP as a guardian. The present paper is devoted to a novel smoothing function method for convex quadratic programming problem
On the Solution of Nonconvex Cardinality Boolean Quadratic Programming problems
"... This paper addresses the solution of a nonlinear boolean quadratic programming problem using three different approaches. The first uses a classic linearization technique to transform the original problem into a Mixed Integer Linear Programming (MILP) problem for which multiple formulations are studi ..."
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This paper addresses the solution of a nonlinear boolean quadratic programming problem using three different approaches. The first uses a classic linearization technique to transform the original problem into a Mixed Integer Linear Programming (MILP) problem for which multiple formulations
Results 1  10
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