Python GA示例

示例#1

文件： bandittechniques.py 项目： jrk/opentuner

    ],
                           name="AUCBanditMetaTechniqueB"))
register(
    AUCBanditMetaTechnique([
        differentialevolution.DifferentialEvolutionAlt(),
        patternsearch.PatternSearch(),
    ],
                           name="AUCBanditMetaTechniqueC"))
register(
    AUCBanditMetaTechnique([
        PSO(crossover='OX3'),
        PSO(crossover='OX1'),
        PSO(crossover='CX'),
        PSO(crossover='PMX'),
        PSO(crossover='PX'),
        evolutionarytechniques.GA(
            crossover='OX3', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='OX1', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='CX', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='PX', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='PMX', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.UniformGreedyMutation(name='ga-base',
                                                     mutation_rate=0.01)
    ],
                           name="PSO_GA_Bandit"))
register(
    AUCBanditMetaTechnique([
        differentialevolution.DifferentialEvolutionAlt(),

示例#2

    ],
                           name="AUCBanditMetaTechniqueB"))
register(
    AUCBanditMetaTechnique([
        differentialevolution.DifferentialEvolutionAlt(),
        patternsearch.PatternSearch(),
    ],
                           name="AUCBanditMetaTechniqueC"))
register(
    AUCBanditMetaTechnique([
        PSO(crossover='op3_cross_OX3'),
        PSO(crossover='op3_cross_OX1'),
        PSO(crossover='op3_cross_CX'),
        PSO(crossover='op3_cross_PMX'),
        PSO(crossover='op3_cross_PX'),
        evolutionarytechniques.GA(
            crossover='op3_cross_OX3', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='op3_cross_OX1', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='op3_cross_CX', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='op3_cross_PX', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.GA(
            crossover='op3_cross_PMX', mutation_rate=0.01, crossover_rate=0.8),
        evolutionarytechniques.UniformGreedyMutation(name='ga-base',
                                                     mutation_rate=0.01)
    ],
                           name="PSO_GA_Bandit"))
register(
    AUCBanditMetaTechnique([
        differentialevolution.DifferentialEvolutionAlt(),