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Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach

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  • Nadav Hallak

    (Tel-Aviv University
    Ecole Polytechnique Federale de Lausanne)

  • Marc Teboulle

    (Tel-Aviv University)

Abstract

This paper introduces a method for computing points satisfying the second-order necessary optimality conditions for nonconvex minimization problems subject to a closed and convex constraint set. The method comprises two independent steps corresponding to the first- and second-order conditions. The first-order step is a generic closed map algorithm, which can be chosen from a variety of first-order algorithms, making it adjustable to the given problem. The second-order step can be viewed as a second-order feasible direction step for nonconvex minimization subject to a convex set. We prove that any limit point of the resulting scheme satisfies the second-order necessary optimality condition, and establish the scheme’s convergence rate and complexity, under standard and mild assumptions. Numerical tests illustrate the proposed scheme.

Suggested Citation

  • Nadav Hallak & Marc Teboulle, 2020. "Finding Second-Order Stationary Points in Constrained Minimization: A Feasible Direction Approach," Journal of Optimization Theory and Applications, Springer, vol. 186(2), pages 480-503, August.
    • Handle: RePEc:spr:joptap:v:186:y:2020:i:2:d:10.1007_s10957-020-01713-x
    DOI: 10.1007/s10957-020-01713-x
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    References listed on IDEAS

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    1. Immanuel M. Bomze & Vaithilingam Jeyakumar & Guoyin Li, 2018. "Extended trust-region problems with one or two balls: exact copositive and Lagrangian relaxations," Journal of Global Optimization, Springer, vol. 71(3), pages 551-569, July.
    2. Tiago Montanher & Arnold Neumaier & Ferenc Domes, 2018. "A computational study of global optimization solvers on two trust region subproblems," Journal of Global Optimization, Springer, vol. 71(4), pages 915-934, August.
    3. Gianni Di Pillo & Stefano Lucidi & Laura Palagi, 2005. "Convergence to Second-Order Stationary Points of a Primal-Dual Algorithm Model for Nonlinear Programming," Mathematics of Operations Research, INFORMS, vol. 30(4), pages 897-915, November.
    4. NESTEROV, Yurii & POLYAK, B.T., 2006. "Cubic regularization of Newton method and its global performance," LIDAM Reprints CORE 1927, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Amir Beck & Dror Pan, 2017. "A branch and bound algorithm for nonconvex quadratic optimization with ball and linear constraints," Journal of Global Optimization, Springer, vol. 69(2), pages 309-342, October.
    6. Francisco Facchinei & Stefano Lucidi, 1998. "Convergence to Second Order Stationary Points in Inequality Constrained Optimization," Mathematics of Operations Research, INFORMS, vol. 23(3), pages 746-766, August.
    7. Minyue Fu & Zhi-Quan Luo & Yinyu Ye, 1998. "Approximation Algorithms for Quadratic Programming," Journal of Combinatorial Optimization, Springer, vol. 2(1), pages 29-50, March.
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    Cited by:

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