Evaluate the chromosome using a fitness function. The result of this evaluation is treated as the “fitness” value as defined by Goldberg (see references).
Galgo object call this method and store the resulted value in order to decide which chromosomes are better choices to be part of the next generation.
The “fitness function” should returns a numeric value scaled from 0 to 1. As close to 1 as better chance it have to be part of the next generation.
The “fitness” function to be called to evaluate all chromosomes. It should follow the format
The original object calling for the evaluation. This is passed when the function is sensitive to data stored in parent object. Commonly it is a
Victor Trevino. Francesco Falciani Group. University of Birmingham, U.K. http://www.bip.bham.ac.uk/bioinf
Goldberg, David E. 1989 Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley Pub. Co. ISBN: 0201157675
For more information see
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