def main():
graph = read_graph_from_file(input_file)
gaParams = GAParams(populationSize=20, noOfGenerations=1000, crossoverProb=0.7, mutationProb=0.15)
problemParams = ProblemParams(network=graph, dim=len(graph), function=calculate_route_length)
ga = GA(gaParams, problemParams)
ga.initialisation()
ga.evaluation()
allBestFitnesses = []
generationsBest = []
overallBest = Chromosome(problemParams)
for generation in range(gaParams.noOfGenerations):
ga.oneGenerationSteadyState()
bestChromo = ga.bestChromosome()
print('Best solution in generation ' + str(generation) + ' f(x) = ' + str(bestChromo.fitness))
allBestFitnesses.append(bestChromo.fitness)
generationsBest.append(bestChromo)
if bestChromo.fitness < overallBest.fitness:
overallBest = bestChromo
print(overallBest.representation)
print(calculate_route_length(overallBest.representation, problemParams.network))
