Welcome to GASolver’s documentation!

Introduction

GASolver is a simple and pure-Python framework for solving problems with genetic algorithms. With its pythonic interface, it allows for a clean implementation of the necessary steps.

It also provides selectors for your population. Currently, the only one available is the Roulette Wheel Selection

Example

Suppose you have defined the necessary attributes for a Genetic Algorithm, that is:

  • A mutation function e.g.: mutation(x)
  • A crossover function e.g.: crossover(x, y)
  • An initial population e.g.: [1, 2, 3]
  • A fitness function e.g.: fitness(x)
  • A goal value e.g.: 42

You can easily create a new instance of GAsolver:

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from ga_solver import GASolver

solver = GASolver(
     initial_pop=initial_pop,
     goal=fitness,
     target_value=maxsize,
     mutation=mutation,
     prob_mutation=0.7,
     crossover_=crossover,
     selector=roullete
 )

for state in solver:  # GASolvers are iterable
   print(f"The current step is {solver.steps}")
   print(f"The best fit so far has value of {solver.best_solution[1]}")
   print(f"The current state is {state}")
   print(f"Population has size {len(problem)}")

API:

Indices and tables