Genetic algorithm formulation and tuning with use of test functions

Abstract

This work discusses single-objective constrained genetic algorithm with floating-point, integer, binary and permutation representation. Floating-point genetic algorithm tuning with use of test functions is done and leads to a parameterization with comparatively outstanding performance.

10 pages, 1 figure, 2 tables. For associated software repository, see https://github.com/ttarkowski/quile