15th EUROPT Workshop on Advances in Continuous Optimization

Montréal, Canada, July 12 — 14, 2017

15th EUROPT Workshop on Advances in Continuous Optimization

Montréal, Canada, July 12 — 14, 2017

Schedule Authors My Schedule
Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402

Derivative Free Optimization 1

Jul 13, 2017 11:30 AM – 12:45 PM

Location: Nancy et Michel-Gaucher

Chaired by Delphine Sinoquet

3 Presentations

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    11:30 AM - 11:55 AM

    A new variable selection strategy for the parallel space decomposition in derivative-free optimization.

    • Nadir Amaioua, presenter, Polytechnique Montréal
    • Charles Audet, GERAD - Polytechnique Montréal
    • Sebastien Le Digabel, Polytechnique Montréal

    The current parallel space decomposition of the Mesh Adaptive Direct Search algorithm (PSD-MADS) is an asynchronous parallel method that uses a simple generic strategy to decompose a problem into smaller dimension subproblems. The present work explores new strategies for selecting the subset of variables defining subproblems to be explored in parallel. These strategies are based on ranking the variables using statistical tools to determine the most influential ones. The statistical approach improves the decomposition of the problem into smaller more relevant subproblems. This work aims to improve the use of available processors.

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    11:55 AM - 12:20 PM

    A Trust Region Method for Solving Derivative-Free Problems with Binary and Continuous Variables Part 1: the underlying algorithm

    • Andrew R. Conn, IBM Research
    • Claudia D'Ambrosio, CNRS
    • Leo Liberti, école polytechnique
    • Delphine Sinoquet, presenter,

    Trust region methods are used to solve various black-box optimization problems, especially when no derivative information is available. In this talk, we will consider an extension of trust region methods for mixed-integer nonlinear programming (MINLP). There are both theoretical and computational innovations to handle the binary variables, including restricting the quadratic model, solving mixed integer quadratic problems and handling well-poisedness. Whereas, of necessity, we address globality with respect to the binary variables, we are content to obtain good local minima for the continuous variables, at least in part because our typical context involves expensive simulations.

  • Cal add eabad1550a3cf3ed9646c36511a21a854fcb401e3247c61aefa77286b00fe402
    12:20 PM - 12:45 PM

    A Trust Region Method for Solving Derivative-Free Problems with Binary and Continuous Variables - Part 2: applications in the energy domain

    • Delphine Sinoquet, presenter,
    • Andrew R. Conn, IBM Research
    • Claudia D'Ambrosio, CNRS
    • Leo Liberti, école polytechnique

    Optimization takes place in many IFPEN applications: inferring the parameters of numerical models from experimental data (earth sciences, combustion in engines, chemical process), design optimization (wind turbine, risers, networks of oil pipelines), optimizing the settings of experimental devices (calibration of engines, catalysis). These typically require minimizing a functional that is complex (nonlinearities, depending on mixed continuous and integer/discrete variables) and expensive to estimate (solution of a numerical model based on differential systems), and for which derivatives are often not available.
    In this talk, we illustrate the potential of the proposed trust region method adapted to binary and continuous variables on several applications in the energy domain.

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