- author = "H.-P. Schwefel",
- title = "Evolving solutions for design and management tasks on computers",
- booktitle = "1999 IEEE International Conference on Systems, Man, and Cybernetics",
- year = "1999",
- volume = "3",
- pages = "573--578",
- address = "Tokyo, Japan",
- month = "12-15 " # oct,
- keywords = "genetic algorithms, genetic programming",
- ISBN = "0-7803-5731-0",
- ISSN = "1062-922X",
-
URL = "
http://hdl.handle.net/2003/5376",
-
URL = "https://ieeexplore.ieee.org/document/823276",
-
DOI = "
10.1109/ICSMC.1999.823276",
- size = "6 pages",
- abstract = "The uninitiated may find it strange that artificial evolution resides among a class of problem solving methods belonging to a field called computational intelligence. Some people still believe that nature's trial-and-error way to adapt subsystems to their environment is a prodigal game at dice that has led to admirable results only due to vast resources of time and space. A rather simple gedanken experiment, however, reveals that all 10/sup 80/ most elementary particles in the universe together with 10/sup 80/ tiniest time steps since the beginning of time cannot explain the development of even simplest bacterial genomes by pure random sampling. Organic evolution must have found a more efficient way to develop clever individuals and manage complex systems. Since about forty years now, a couple of scientists have tried to mimic this process, and they have learned to exploit some tricks of life for solving an amazing variety of design and management tasks. The paper tries to give an overview of some applications as well as a summary of what we know about the general behaviour of evolutionary algorithms.",
-
notes = "Cat. No.99CH37028
Also known as \cite{823276}",
