Genetic Algorithm in C++ with template metaprogramming and abstraction for constrained optimization
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Updated
Feb 4, 2020 - C++
Genetic Algorithm in C++ with template metaprogramming and abstraction for constrained optimization
Pipeline to prepare alignments for visualization with ACT (goo.gl/1T28jX) and for locating possible inter-chromosomal re-arrengments/misjoints
The library provides a general genetic algorithm. It is simple, easy to use, and very fast. All you need to do is to define the fitness function and its variables. There are many examples of how to deal with classic genetic algorithms problems.
This program implements a genetic algorithm for curve fitting using a polynomial equation. The goal is to find the best coefficients for the polynomial equation that minimize the distance between the curve and a given set of data points. The genetic algorithm is used to search for the optimal solution by evolving a population of candidate solutions
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