Genetic algorithm is one of the more popular evolutionary algorithm with wide range of usage including optimization. While there are a lot of implementation of this technique, including the one as an option in the Excel solver, building one is a very good choice to understand the underlying process.

The TI Nspire provided a rich set of matrix operations that can be utilized to model the data structure required genetic algorithm. For example, creating an initial population with arbitrary size of binary, integer, or real numbers.

The cross over operation can be modeled as extracting part of a matrix using the augment function.

Fitness function can be dynamically defined using the expr function available in the Nspire environment.