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Solution methods for optimization problems

  From Monday 12 June 2017 to Wednesday 14 June 2017

  Training    

Announced
Deadline for registration: 15 days before the starting date of each training
Duration : 3 days / (21 hours)

CANCELLED

 

 

Abstract

In this training course, modern methods for solving optimization problems are detailed. Newton or Quasi-Newton methods for the solution of unconstrained minimization problems are first addressed. Globalization techniques such as trust region methods or adaptive cubic regularization are then detailed. Methods for solving problems without derivatives and problem with general constraints are also outlined. Finally, the solution of nonlinear least-squares problems arising in large-scale inverse problems with application to Earth sciences are reviewed.

Target participants

Engineers, physicists, computer scientists and numerical
analysts who wish to develop basic knowlegde to solve optimisation problems.

Prerequisites

Basic knowledge in linear algebra, numerical analysis and geometry.

Scientific contact : Serge GRATTON

Fee

  • Trainees/PhDs/PostDocs : 150 €
  • CERFACS shareholders/CNRS/INRIA : 450 €
  • Public : 900 €

Program

(Every day from 9h to 17h30)

Day 1

  1. Examples of industrial optimization problems.
  2. Crucial points for optimization problems modeling: characteristics of the cost function and constraints, importance of the convexity, scaling of the variables and curse of dimensionality for global optimization.
  3. Optimality conditions for unconstrained optimization problems.
  4. Hands on exercises in Matlab
  5. Reverse amphi: the participants introduce their optimization issues and the training team proposes possible relevant solution methods.

Day 2

  1. Theory of Lagange multipliers for constrained optmisation.
  2. Optimisation methods using interior or exterior penalty approaches and projection approaches.
  3. Hands on session in Matlab: augmented Lagrangian method.
  4. Reverse amphi: the participants introduce their optimization issues and the training team proposes possible relevant solution methods.

Day 3

  1. Derivative free optimisation in 1D.
  2. Generalization and introduction to model-based and direct-search methods.
  3. Hands on exercises in Matlab.

CALENDAR

Monday

11

December

2023

Multi-architecture parallelism using Kokkos/C++ library

From Monday 11 December 2023 at 14h00 to Wednesday 13 December 2023 at 17h00

  Training    

Thursday

21

December

2023

PhD Defense : Aurélien LINÉ : ” Modulation of European near-term climate change by multi-decadal internal variability “

Thursday 21 December 2023 at 15h00

  CERFACS - Toulouse - France     Organized by Nathalie BROUSSET    

Monday

18

March

2024

Introduction to programming practices for scientific computing

Monday 18 March 2024

  Training    

ALL EVENTS