robinlabuji/geneticalgorithm

Genetic Algorithms with pyevolve

Pyevolve was developed to be a complete genetic algorithm framework written in pure python. The main objectives were:

• written in pure python, to maximize the cross-platform issue;
• easy to use API;
• see the evolution, the user can and must see and interact with the evolution statistics, graphs, etc;
• extensible, the user can create new representations, genetic operators like crossover, mutation, etc;
• fast, the design must be optimized for performance;
• common features, the framework must implement the most common features: selectors like roulette wheel, tournament, ranking, uniform; scaling schemes like linear scaling, etc;
• default parameters, we must have default operators, settings, etc in all options;
• open-source, the source is for everyone, not for only one.

Aim of these notebooks

You will learn the basic functioning of Pyevolve. You will make scripts for using genetic algorithms in simple problems.

• First Example
• Graphical Analysis
• Rastrigin Function
• Travelling Salesman Problem