| Differential Evolution |
Article Index for Differential |
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Information AboutDifferential Evolution |
| CATEGORIES ABOUT DIFFERENTIAL EVOLUTION | |
| optimization algorithms | |
| evolutionary algorithms | |
| algorithms | |
| optimization | |
| operations research | |
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The "DE community" has been growing since 1994 - 1996 and ever more researchers are working on and with DE. DE is a very simple population based, stochastic function minimizer which is very powerful at the same time. DE managed to finish 3rd at the First International Contest on Evolutionary Computation (1st ICEO) which was held in Nagoya, may 1996. DE turned out to be the best genetic type of algorithm for solving the real-valued test function suite of the 1st ICEO (the first two places were given to non-GA type algorithms which are not universally applicable but solved the test-problems faster than DE). The crucial idea behind DE is a scheme for generating trial parameter vectors. Basically, DE adds the weighted difference between two population vectors to a third vector. This way no separate probability distribution has to be used which makes the scheme completely self-organizing. Further information on DE can be found in . SEE ALSO EXTERNAL LINKS |
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