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High level optimization routines in Fortran 95 for optimization problems using a genetic algorithm
with elitism, steady-state-reproduction, dynamic operator scoring by merit, no-duplicates-in-population. Chromosome representation may be integer-array, real-array, permutation-array, character-array.
Single objective and multi-objective maximization routines are present. Possible to incorporate own crossover and mutation operators exclusively or in addition to standard operators that are included by default.
The aim is to make it possible to quickly develop a high performance GA for any given application problem.
Features
- elitism
- no duplicates in population
- dynamic operator selection probabilities based on recent performance
- steady state reproduction
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