2024-10-18 09:44:43 +02:00
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#/bin/python
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import random
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tasks = [4, 5, 8, 2, 10, 7]
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sol1=[1, 0, 1, 1, 0, 1]
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sol2=[0, 0, 1, 0, 1, 1]
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def generate_initial_population(problem_data, k, popsize):
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return [[random.randint(0, k-1) for _ in range(len(problem_data))] for _ in range(popsize)]
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def fitness(solution, problem_data, k):
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return max([sum(problem_data[i] for i in range(len(solution)) if solution[i] == j) for j in range(k)])
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def crossover(solutionA, solutionB):
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return [solutionA[i] if i % 2 == 0 else solutionB[i] for i in range(len(solutionA))]
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def mutation(solution, k):
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i = random.randint(0,len(solution)-1)
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solution[i] = random.choice(list({i for i in range(k)} - {solution[i]}))
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return solution
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