Journées de l'optimisation 2016

HEC Montréal, Québec, Canada, 2 — 4 mai 2016

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MB1 Exposé magistral II / Tutorial II

2 mai 2016 15h30 – 17h10

Salle: Banque Scotia

Présidée par Sebastien Le Digabel

1 présentation

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    15h30 - 17h00

    Derivative-free optimization

    • Warren Hare, prés., UBC

    Derivative-free optimization refers to the development, study, and application of algorithms to solve optimization problems without using (sub-)gradient evaluations. Applications are rich, and include almost any problem where the objective function is provided via a computer simulation. In this introductory lecture, we will aim to examine 3 popular methods: Genetic Algorithms, Pattern Search Methods, and Simplex Gradient Descent. We will highlight the strengths and weaknesses of each, and compare the three on a real-world application.

    This tutorial will teach under the assumption that the audience is comfortable with: Linear Algebra (matrix manipulation), Multivariate Calculus, and Numerical Analysis (notably, Taylor's Theorem).

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