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The generational process was repeated with a [https://en.wikipedia.org/wiki/Crossover_(genetic_algorithm) crossover] probability of 0.5
and a [https://en.wikipedia.org/wiki/Mutation_(genetic_algorithm) mutation probability] of 0.001. Fitness scaling
<ref>[[David E. Goldberg]] ('''1989'''). ''Genetic Algorithms in Search, Optimization, and Machine Learning''. [https://en.wikipedia.org/wiki/Addison-Wesley Addison-Wesley], pp. 76-80</ref> <ref>[https://www.mathworks.com/help/gads/fitness-scaling.html Fitness Scaling - MATLAB & Simulink]</ref>
was used to enhance the fittest members' fitness in each generation to twice the average fitness while keeping the average the same.
