#/bin/python
import random

tasks = [4, 5, 8, 2, 10, 7]
sol1=[1, 0, 1, 1, 0, 1]
sol2=[0, 0, 1, 0, 1, 1]

def generate_initial_population(problem_data, k, popsize):
    return [[random.randint(0, k-1) for _ in range(len(problem_data))] for _ in range(popsize)]

def fitness(solution, problem_data, k):
    return max([sum(problem_data[i] for i in range(len(solution)) if solution[i] == j) for j in range(k)])

def crossover(solutionA, solutionB):
    return [solutionA[i] if i % 2 == 0 else solutionB[i] for i in range(len(solutionA))]

def mutation(solution, k):
    i = random.randint(0,len(solution)-1)
    solution[i] = random.choice(list({i for i in range(k)} - {solution[i]}))
    return solution