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Genetic Algorithm implementation in Python for the Traveling Salesman Problem

The main script is the ga.py file which contains base classes for creating your own Genetic Algorithm (i.e. import ga; env = ga.Environment(kind=YourKind) where YourKind is some class inheriting ga.IndividualBase) or for simply running the provided implementation of the Traveling Salesman Problem.

Usage for the latter:

Usage: ga.py [options]

Options:
-h, --help            show this help message and exit
-g MAX_GENERATIONS, --max-generations=MAX_GENERATIONS
                        Continue till we have reached MAX_GENERATIONS
-p POPULATION_SIZE, --population-size=POPULATION_SIZE
                        Store POPULATION_SIZE different individuals
-c CROSSOVER_RATE, --crossover-rate=CROSSOVER_RATE
                        Set crossover probability to CROSSOVER_RATE (between 0
                        and 1)
-m MUTATION_RATE, --mutation-rate=MUTATION_RATE
                        Set mutation probability to MUTATION_RATE (between 0
                        and 1)
-e ELITISM, --elitism=ELITISM
                        Enable elitism for the top ELITISM results
--print-interval=PRINT_INTERVAL
                        Print intermediate results for every PRINT_INTERVAL
                        generations. Use 0 for no intermediate output
--csv=CSV             Return csv output for easy plotting every CSV
                        generation
--csv-file=CSV_FILE   Where to write the csv output to (defaults to STDOUT)
-s SAMPLES, --samples=SAMPLES
                        The amount of samples to use. Very useful with csv
                        output
--processes=PROCESSES
                        By default the samples are calculated in parallel, you
                        can change the amount of simultaneous processes with
                        PROCESSES

To generate all output automatically there is also a script called generate_charts.sh available which automatically try all kinds of different values for elitism, population, mutation and crossover.

If you have any questions, feel free to mail me at: Rick _at_ Fawo _dot_ nl