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Piecewise Convex Maximization Problems: Piece Adding Technique

Author

Listed:
  • Dominique Fortin

    (INRIA)

  • Ider Tseveendorj

    (Université de Versailles St.Quentin en Yvelines)

Abstract

In this article, we provide a global search algorithm for maximizing a piecewise convex function F over a compact D. We propose to iteratively refine the function F at local solution y by a virtual cutting function p y (⋅) and to solve max {min {F(x)−F(y),p y (x)}∣x∈D} instead. We call this function either a patch, when it avoids returning back to the same local solutions, or a pseudo patch, when it possibly yields a better point. It is virtual in the sense that the role of cutting constraints is played by additional convex pieces in the objective function. We report some computational results, that represent an improvement on previous linearization based techniques.

Suggested Citation

  • Dominique Fortin & Ider Tseveendorj, 2011. "Piecewise Convex Maximization Problems: Piece Adding Technique," Journal of Optimization Theory and Applications, Springer, vol. 148(3), pages 471-487, March.
    • Handle: RePEc:spr:joptap:v:148:y:2011:i:3:d:10.1007_s10957-010-9763-5
    DOI: 10.1007/s10957-010-9763-5
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    Cited by:

    1. Manlio Gaudioso & Giovanni Giallombardo & Giovanna Miglionico, 2018. "Minimizing Piecewise-Concave Functions Over Polyhedra," Mathematics of Operations Research, INFORMS, vol. 43(2), pages 580-597, May.

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