16-th September 2007

Registered participants: Austria (1), Bulgaria (1), Croatia (3), Czech Republic (3), France (3), Germany (3), India (5), Italy (2), New Zealand (1), Poland (13), Russian Federation (2), Slovenia (1), South Korea (6), Spain (1), Sweden (1), Switzerland (1), Taiwan (3), Turkey (2), Ukraine (1), United Kingdom (5), USA (1).

The genetic algorithms can be applied for solving the global optimisation tasks. These methods mimick the evolution of plants and animals. The one-day workshop called " Genetic algorithms for beginners", is intended to:

- provide a basic course of genetic methods of global optimisation to those who are not yet familiar with them and to those who wish to systematise or extend their basic knowledge,

- promote such methods among materials scientists.

The lectures will be given on 16-th September 2007, mainly by materials scientists, physicists, chemists and crystallographers (typically: Symposium-G lecturers) who already have implemented such computational methods within their own fields.

The proposed topics:
- explanation of basic ideas & concepts of construction and writing of genetic algorithms
- design and implementation of genetic algorithms,
- variables: discrete or continuous?
- coding methods
- parameter values: universal or problem specific?
- convergence criteria
- genetic operators (mutation, selection, crossover...)
- advantages of combined methods (hybrid methods, joining with neural
networks, etc...)
- multiobjective methods
- parallel computation
- ready to use software (in particular - to be presented by the software authors, suppliers or users)
- real implementation of GA using an open source software
- materials scientist's view on the genetic approach

A part of lectures will be directed to presentation of simple instructive examples of application in materials science (catalysis, clusters, proteins...) in order to show the simplicity and power of the genetic approach (for subjects see the lectures list).


Programme Committee:

Chairmen: Wojciech Paszkowicz (Warsaw, Poland), Kenneth D.M. Harris (Cardiff, Wales, UK)

Members: Nirupam Chakraborti ( Kharagpur, India), Pierre Collet (Calais, France) , Roy L. Johnston (Birmingham, UK)

Workshop lecturers:

1. Manfred Baerns, Dept. of Inorganic Chemistry, Fritz-Haber-Institute of Max-Planck-Gesellschaft,  Berlin (Dahlem), Germany

2. Nirupam Chakraborti, Dept. of Metallurgical & Materials Engineering, Indian Institute of Technology, Kharagpur, India

3. Pierre Collet, (1) Laboratoire d'Informatique du Littoral, Université du Littoral Côte d'Opale (ULCO), Centre Universitaire de la Mi-Voix, Calais, France (until August 2007); (2) LSiiT Laboratory, University of Strasbourg, Strasbourg, France (since September 2007)

4. David Farrusseng, Institut de Recherches sur la Catalyse, CNRS, Villeurbanne, France

5. Marek W. Gutowski, Institute of Physics, Polish Academy of Sciences, Warsaw, Poland

6. Roy L. Johnston, School of Chemistry, University of Birmingham, Birmingham, UK

7. Jooyoung Lee, School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea

8. El-Ghazali Talbi, Laboratoire d'Informatique Fondamentale de Lille - UMR CNRS, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France

9. Scott M. Woodley, Davy Faraday Reseach Laboratory (DFRL), KLB, Gower Street, London WC1E6BT, United Kingdom

(Updated 3-nd August 2007).



Nirupam Chakraborti

Genetic algorithms: Explanation of basic ideas. Part 1: The single objective approach

Pierre Collet
Genetic algorithms: operators and parameters

Marek W. Gutowski
Gentle but rigorous introduction to genetic algorithms or what makes them tick?

El-Ghazali Talbi
Evolutionary algorithms: From design to implementation

Nirupam Chakraborti 

Genetic algorithms: Explanation of basic ideas. Part 2: Multi-objective methods

Pierre Collet
Genetic programming


Roy L. Johnston
Genetic algorithms for cluster optimization - general aspects

Jooyoung Lee
Global optimization and protein folding studies

Nirupam Chakraborti

Genetic algorithms: Explanation of basic ideas. Part 3:  Genetic algorithm-neural net combination

Manfred Baerns
Application of genetic algorithms in the development of catalytic inorganic materials


David Farrusseng
Implement your Genetic Algorithms with a mouse

(attendants' notebooks recommended)

Scott M. Woodley                    
Hands-on guide for breeding structures using GULP

(attendants' notebooks recommended)



10:15 - 10:30  OPENING

10:30 - 12:00  lectures (3x30 min)

12:00 - 12:15  coffee break

12:15 - 13:15  lectures (2x30 min)

13:15 - 14:30  lunch

14:30 - 16:00  lectures (3x30 min)

16:00 - 16:15  coffee break

16:15 - 18:15  lectures (4x30 min)

about 18:40     arrival to the registration desk at the main site

(selected books and conference proceedings in English and Polish):

  1. D.E. Clark, Evolutionary Algorithms in Molecular Design (Wiley-VCH 2000)
  2. L. Davis, Genetic Algorithms and Simulated Annealing (Morgan Kaufmann 1988)
  3. M. Gen, R. Cheng,  Genetic Algorithms and Engineering Design (Wiley 1997)
  4. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning (Addison-Wesley1989)
  5. M.W. Gutowski, Biology, Physics, Small Worlds and Genetic Algorithms, in: Leading Edge Computer Science Research, S. Shannon (ed.), (Nova Publishers 2005), pp. 165–218
  6. J.H. Holland, Adaptation in Natural and Artificial Systems (Univ. of Michigan Press 1975; MIT Press 1992)
  7. J.R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection (MIT Press 1992)
  8. J.R. Koza, Genetic Programming II: Automatic Discovery of Reusable Programs (MIT Press 1994)
  9. Z. Michalewcz, Genetic Algorithms + Data Structures = Evolution Programs, 3-rd edition (Springer 1996)
  10. W.M. Spears, Evolutionary Algorithms: The Role of Mutation and Recombination (Springer 2000)
  11. K. Watanabe, M.M.A. Hashem, Evolutionary Computations: New Algorithms and Their Applications to Evolutionary Robots (Springer 2004)  
  1. Applications of Evolutionary Computing, G.R. Raidl, S. Cagnoni, J. Branke, D. Corne, R. Drechsler, Y. Jin, C.G. Johnson, P. Machado, E. Marchiori, F. Rothlauf, G.D. Smith, G. Squillero (eds.), (Springer 2004)
  2. Applications of Evolutionary Computation in Chemistry, R.L. Johnston (ed.), (Springer 2004)
  3. Foundations of Genetic Algorithms, vol. 5, C.R. Reeves, W. Banzhaf (eds.), (Morgan Kaufmann 1999)
  4. Genetic Algorithms in Engineering Systems, A.M.S. Zalzala, P.J. Fleming (eds.), (IEE 1997)Handbook of Genetic Algorithms, L. Davis (ed.), (Van Nostrand Reinhold 1991)
  5. Industrial Applications of Genetic Algorithms, C.L. Karr, L.M. Freeman (eds.), (CRC Press 1997)
  6. Practical Handbook of Genetic Algorithms, L. Chambers (ed.), (CRC Press 1999)  
  7. Proceedings of COGANN Workshop (International Workshop on Combinations of Genetic Algorithms and Neural Networks), IJCNN, Baltimore, D. Whitley (ed.), (IEEE Computer Society Press 1992)
  8. Evolutionary Algorithms in Engineering and Computer Science, K.M. Miettinen, M.M. Makela, P. Neittaanmaki, J. Periaux (eds.), (Wiley 1999)


  1. J. Arabas, Wykłady z algorytmów ewolucyjnych (WNT 2001)
  2. R. Galar, Miękka selekcja w losowej adaptacji globalnej w R n. Próba biocybernetycznego ujęcia rozwoju (Univ. of Technology of Wrocław 1990)
  3. D.E. Goldberg, Algorytmy genetyczne i ich zastosowania (WNT 1995, 2003)
  4. T.D. Gwiazda, Algorytmy genetyczne. Wstęp do teorii (TDG 1995)
  5. T.D. Gwiazda, Algorytmy genetyczne. Kompendium. Tom 1 (PWN 2007)
  6. Z. Michalewicz, Algorytmy genetyczne + Struktury danych = Programy ewolucyjne (WNT 1996)
  7. D. Rutkowska, M. Piliński, L. Rutkowski, Sieci neuronowe, algorytmy genetyczne i systemy rozmyte (WNT 1997)

Proceedings of Polish Conferences KAEiOG "Evolutionary Algorithms and Global Optimisation" ( published by Warsaw University of Technology):

  1. Materiały I Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Murzasichle 12.06-15.06.1996
  2. Materiały II Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Rytro 15.09-19.09.1997
  3. Materiały III Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Potok Złoty, 25-28.05.1999 
  4. Materiały IV Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Lądek Zdrój, 5.06-8.06.2000
  5. Materiały V Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Jastrzębia Góra, 30.05.-2.06.2001,
  6. Materiały VI Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Łagów Lubuski, 26.05-28.05.2003
  7. Materiały VII Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Kazimierz Dolny, 24.05-26.05.04
  8. Materiały VIII Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Korbielów, 30.05-01.06.05
  9. Materiały IX Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Murzasichle, 31.05-2.06.2006.
  10. Materiały X Krajowej Konferencji KAEiOG "Algorytmy Ewolucyjne i Optymalizacja Globalna", Będlewo, 11.06-13.06.2007

The WORKSHOP attendees wishing to actively participate in the tutorial lecture by David Farruseng can download and install OptiCat software at the following address. Files corresponding to case studies (which will be used for tutorial purposes) can also been downloaded as well as videos and slides.



Wojciech Paszkowicz, Institute of Physics, Polish Academy of Sciences, Warsaw, Poland

Kenneth D.M. Harris, School of Chemistry, Cardiff University, Wales


Wojciech Paszkowicz
Institute of Physics
Polish Academy of Sciences
Al. Lotnikow 32/46
PL-02-668 Warsaw


Kenneth D.M. Harris
School of Chemistry
Cardiff University
Park Place
CF10 3AT Wales