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Séance TC11 - Algorithmes pratiques de recherche directe / Practical Methods of Direct Search

Jour mardi, le 05 mai 2009
Salle Demers Beaulne
Président Charles Audet

Présentations

15h30-
15h55
Black-Box Optimization with the NOMAD Software
  Sébastien Le Digabel, GERAD, École Polytechnique de Montréal, Mathématiques et génie industriel, C.P. 6079, Succ. Centre-ville, Montréal, Québec, Canada, H3C 3A7
Charles Audet, GERAD, École Polytechnique de Montréal, Mathématiques et génie industriel, C.P. 6079, Succ. Centre-ville, Montréal, Québec, Canada, H3C 3A7

NOMAD is a black-box optimization software. The functions representing the objective and constraints of such problems have no exploitable structure (such as derivatives). They are typically evaluated by computer codes. The presentation gives an overview of the Mesh Adaptive Direct Search algorithm and describes the NOMAD implementation and its use.


15h55-
16h20
Station Location for Snow-Water Equivalent Measurement
  Stéphane Alarie, IREQ, Canada

Hydroelectric reservoirs management requires precise estimation of snow quantity, that becomes a natural inflow in spring. Snow quantity are measured at fixed sites by GMON devices. Krieging interpolation estimates the quantity of snow over the territory and provides an error approximation. We use the recent MADS algorithm to identify the optimal GMON positioning that minimizes the prediction error.


16h20-
16h45
Algorithmic Parameter Optimization
  Cong-Kien Dang, GERAD, École Polytechnique de Montréal, Canada
Dominique Orban, GERAD et École Polytechnique de Montréal, Mathématiques et génie industriel, C.P. 6079, Succ. Centre-ville, Montréal, Québec, Canada, H3C 3A7
Charles Audet, GERAD, École Polytechnique de Montréal, Mathématiques et génie industriel, C.P. 6079, Succ. Centre-ville, Montréal, Québec, Canada, H3C 3A7

Identification of good algorithmic parameters may be formulated as a black-box optimization problem, and solved using a direct search algorithm. The present work refines this idea to increase the flexibility and emphasize on the black box separation into two components representing the data and structure. We apply it to the derivative-free algorithm of Conn-Scheinberg-Toint.


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