CIMPA School, course on:

"NUMERICAL OPTIMIZATION
APPLICATIONS IN CFD"

Laurent Dumas
 

DATES AND LOCATION:  from September, 3rd to September 5th, 2007, University of Ateneo, Manilla, CIMPA school
OUTLINE OF THE COURSE :

1.  Introduction: the car drag reduction problem    (course #1)    

2. Numerical Optimization: main tools
    2.1 Descent methods with linesearch strategies
    2.2 Evolutionary Algorithms                                  (course #2)    
    2.3 Hybrid methods and surrogate models

3. First Applications of Numerical Optimization   (course #3)        
    3.1 The I-Beam problem
    3.2 The LJ problem
    3.3 The Fiber Bragg Grating Problem

4. CFD-based Optimization                                  (course #4)    
    4.1 The Navier-Stokes equation
    4.2 Shape optimization in aeronautics
    4.3 The car drag reduction problem



 
BIBLIOGRAPHY:

Numercial optimization, theoretical and practical aspects: JF Bonnans, JC Gilbert, C. Lemaréchal, C. Sagastizbal, Springer Verlag 2003.
Genetic Algorithms on search, optimization and machine learning: D. Goldberg, 1989
Multi-Objective Optimization Using Evolutionary Algorithms, K. Deb, 2001

ON THE WEB:

    Theoretical part:    
    A tutorial 'How to build an avolutionary algorithm' by the EVONET community
    An introduction article on 'Evolution strategies' by HG Beyer and HP Schweifel
    An online course on 'Numerical Optimization' at Oxford University
    An online course on 'Optimization inengineering design' at  the Georgia Institute of Technology
    A book  Numerical recipes in C or Fortran 77 (Chapter 10 mainly)
    An introduction article on 'Numerical Solution of Optimization Test-Cases by Genetic Algorithms' by N. Marco and J.A. Desideri

    Applicative part:
    Description of the I-Beam problem
     Robust optimization of the I-Beam
    A short tutorial 'Introduction to Fiber Bragg Gratings'
    A talk  'Optimisation of optical communication systems by means of genetic algorithms' by myself
    A PhD dissertation “Synthesis and characterization of fiber Bragg gratings” by J. Skaar  (chapters 2 and 3.1 mainly)
    An article 'Real-coded genetic algorithm for Bragg grating parameter synthesis' by G. Cormier and R. Boudreau
    An article 'Multi-objective and constrained design of fibre Bragg gratings using evolutionary algorithms' by S. Manos and L. Poladian
    An article "Semi deterministic vs Genetic Algorithms for global optimization of multichannel optical filters" by myself,  B. Ivorra, B. Mohammadi, P. Redont and O. Durand
    Articles on the LJ problem: article 1 article 2, article 3, article 4  thesis
    

 
SCILAB PROGRAMS
 
     All theScilab programs presented during this course can be found here