特殊

自定義評價函數

同前

def evalKnapsack(individual):weight = 0.0value = 0.0for item in individual:weight += items[item][0]value += items[item][1]if len(individual) > MAX_ITEM or weight > MAX_WEIGHT:return 10000, 0 # Ensure overweighted bags are dominatedreturn weight, value,

自定義交叉函數

def cxSet(ind1, ind2):"""Apply a crossover operation on input sets. The first child is theintersection of the two sets, the second child is the difference of thetwo sets."""temp = set(ind1) # Used in order to keep typeind1 &= ind2 # Intersection (inplace)ind2 ^= temp # Symmetric Difference (inplace)return ind1, ind2

&=,^= python中的位運算符
建議在新標簽頁打開圖片

自定義變異函

def mutSet(individual):"""Mutation that pops or add an element."""if random.random() < 0.5:if len(individual) > 0: # We cannot pop from an empty setindividual.remove(random.choice(sorted(tuple(individual))))else:individual.add(random.randrange(NBR_ITEMS))return individual,

使用短版本的遺傳算法

def main():random.seed(64)NGEN = 50MU = 50LAMBDA = 100CXPB = 0.7MUTPB = 0.2pop = toolbox.population(n=MU)hof = tools.ParetoFront()stats = tools.Statistics(lambda ind: ind.fitness.values)stats.register("avg", numpy.mean, axis=0)stats.register("std", numpy.std, axis=0)stats.register("min", numpy.min, axis=0)stats.register("max", numpy.max, axis=0)algorithms.eaMuPlusLambda(pop, toolbox, MU, LAMBDA, CXPB, MUTPB, NGEN, stats,halloffame=hof)return pop, stats, hof

此處與之前的文章效果類似
- 粒子群優化算法
- 短版本可以參考官網介紹

源代碼

#!usr/bin/env python #-*- coding:utf-8 _*- """ @author:fonttian @file: knapsackProblem.py @time: 2017/10/15 """ # This file is part of DEAP. # # DEAP is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as # published by the Free Software Foundation, either version 3 of # the License, or (at your option) any later version. # # DEAP is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with DEAP. If not, see <http://www.gnu.org/licenses/>.import randomimport numpyfrom deap import algorithms from deap import base from deap import creator from deap import toolsIND_INIT_SIZE = 5 # 基因編碼位數 MAX_ITEM = 50 MAX_WEIGHT = 50 NBR_ITEMS = 20# To assure reproductibility, the RNG seed is set prior to the items # dict initialization. It is also seeded in main(). random.seed(64)# Create the item dictionary: item name is an integer, and value is # a (weight, value) 2-uple. items = {} # Create random items and store them in the items' dictionary. for i in range(NBR_ITEMS):items[i] = (random.randint(1, 10), random.uniform(0, 100))creator.create("Fitness", base.Fitness, weights=(-1.0, 1.0)) creator.create("Individual", set, fitness=creator.Fitness)toolbox = base.Toolbox()# Attribute generator toolbox.register("attr_item", random.randrange, NBR_ITEMS)# Structure initializers toolbox.register("individual", tools.initRepeat, creator.Individual,toolbox.attr_item, IND_INIT_SIZE) toolbox.register("population", tools.initRepeat, list, toolbox.individual)def evalKnapsack(individual):weight = 0.0value = 0.0for item in individual:weight += items[item][0]value += items[item][1]if len(individual) > MAX_ITEM or weight > MAX_WEIGHT:return 10000, 0 # Ensure overweighted bags are dominatedreturn weight, value,def cxSet(ind1, ind2):"""Apply a crossover operation on input sets. The first child is theintersection of the two sets, the second child is the difference of thetwo sets."""temp = set(ind1) # Used in order to keep typeind1 &= ind2 # Intersection (inplace)ind2 ^= temp # Symmetric Difference (inplace)return ind1, ind2def mutSet(individual):"""Mutation that pops or add an element."""if random.random() < 0.5:if len(individual) > 0: # We cannot pop from an empty setindividual.remove(random.choice(sorted(tuple(individual))))else:individual.add(random.randrange(NBR_ITEMS))return individual,toolbox.register("evaluate", evalKnapsack) toolbox.register("mate", cxSet) toolbox.register("mutate", mutSet) toolbox.register("select", tools.selNSGA2)def main():random.seed(64)NGEN = 50MU = 50LAMBDA = 100CXPB = 0.7MUTPB = 0.2pop = toolbox.population(n=MU)hof = tools.ParetoFront()stats = tools.Statistics(lambda ind: ind.fitness.values)stats.register("avg", numpy.mean, axis=0)stats.register("std", numpy.std, axis=0)stats.register("min", numpy.min, axis=0)stats.register("max", numpy.max, axis=0)algorithms.eaMuPlusLambda(pop, toolbox, MU, LAMBDA, CXPB, MUTPB, NGEN, stats,halloffame=hof)return pop, stats, hofif __name__ == "__main__":pop, stats, hof = main()print("最佳裝包為(最佳個體) :",hof[-1])print(len(pop))print(len(hof))print("最佳裝包時的重量與價值(最佳適應度) :",evalKnapsack(hof[-1])) 《新程序員》：云原生和全面數字化實踐50位技術專家共同創作，文字、視頻、音頻交互閱讀

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