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Generalized Convex Multiplicative Programming via Quasiconcave Minimization

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Abstract

We present a new method for minimizing the sum of a convex function and aproduct of k nonnegative convex functions over a convex set. This problem isreduced to a k-dimensional quasiconcave minimization problem which is solvedby a conical branch-and-bound algorithm. Comparative computational results areprovided on test problems from the literature.

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Authors and Affiliations

  1. GERAD & Département de Mathématiques et de Génie Industriel, Ecole Polytechnique de Montréal, C.P. 6079, succ. Centre-ville, Montréal (, Québec), H3C 3A7, Canada

    Brigitte Jaumard

  2. Département de Mathématiques et de Génie Industriel, Ecole Polytechnique de Montréal, C.P. 6079, succ. Centre-ville, Montréal (, Québec), H3C 3A7, Canada

    Christophe Meyer

  3. Institute of Mathematics, P.O. Box 631, Bo Ho, Hanoi, Vietnam

    Hoang Tuy

Authors
  1. Brigitte Jaumard
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  2. Christophe Meyer
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  3. Hoang Tuy
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Jaumard, B., Meyer, C. & Tuy, H. Generalized Convex Multiplicative Programming via Quasiconcave Minimization. Journal of Global Optimization 10, 229–256 (1997). https://doi.org/10.1023/A:1008203116882

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