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A Modified Projection Algorithm for Large Strictly-Convex Quadratic Programs

Author

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  • V. Ruggiero

    (University of Ferrara)

  • L. Zanni

    (University of Modena and Reggio Emilia)

Abstract

In this paper, we propose a modified projection-type method for solving strictly-convex quadratic programs. This iterative scheme requires essentially the solution of an easy quadratic programming subproblem and a matrix-vector multiplication at each iteration. The main feature of the method consists in updating the Hessian matrix of the subproblems by a convenient scaling parameter. The convergence of the scheme is obtained by introducing a correction formula for the solution of the subproblems and very weak conditions on the scaling parameter. A practical nonexpensive updating rule for the scaling parameter is suggested. The results of numerical experimentation enable this approach to be compared with some classical projection-type methods and its effectiveness as a solver of large and very sparse quadratic programs to be evaluated.

Suggested Citation

  • V. Ruggiero & L. Zanni, 2000. "A Modified Projection Algorithm for Large Strictly-Convex Quadratic Programs," Journal of Optimization Theory and Applications, Springer, vol. 104(2), pages 255-279, February.
  • Handle: RePEc:spr:joptap:v:104:y:2000:i:2:d:10.1023_a:1004605612267
    DOI: 10.1023/A:1004605612267
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    References listed on IDEAS

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    1. Stella Dafermos, 1980. "Traffic Equilibrium and Variational Inequalities," Transportation Science, INFORMS, vol. 14(1), pages 42-54, February.
    2. Caroline Fisk & Sang Nguyen, 1982. "Solution Algorithms for Network Equilibrium Models with Asymmetric User Costs," Transportation Science, INFORMS, vol. 16(3), pages 361-381, August.
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    Cited by:

    1. Zhe Liu & Yahya Fathi, 2011. "An active index algorithm for the nearest point problem in a polyhedral cone," Computational Optimization and Applications, Springer, vol. 49(3), pages 435-456, July.
    2. Zhe Liu & Yahya Fathi, 2012. "The nearest point problem in a polyhedral set and its extensions," Computational Optimization and Applications, Springer, vol. 53(1), pages 115-130, September.

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