进化算法 遗传算法课件.pptVIP

1.IntroductiontoGeneticAlgorithms;优化问题;例：无约束单目标，多峰;约束单目标;约束多目标;TSP;TSP;传统最优化面临新挑战：实际问题;优化问题的复杂性;问题的复杂度;PolynomialandExponentialComplexity;PolynomialandExponentialComplexity;;;随机算法：爬山法;;易陷入局部最优;1.IntroductionofGeneticAlgorithms;1.IntroductionofGeneticAlgorithms;1.IntroductionofGeneticAlgorithms;进化论;Lamarck进化论;Darwin进化论;孟德尔学说;;比较;新达尔文主义;;生物学中的遗传概念;生物学中的遗传概念;EvolutionasProblemSolving;EvolutionasaProblemSolvingMethod;

Lesson1:Keepapopulation/collectionofdifferentthingsonthego.

Lesson2:Select`parents’witharelativelyweakbiastowardsthefittest.

It’snotreallyplainsurvivalofthefittest,whatworksis

thefitteryouare,themorechanceyouhavetoreproduce,

anditworksbestifeventheleastfitstillhavesomechance.

（无偏见的选择父代，或适者生存)

Lesson3:Itcansometimeshelptouserecombinationoftwoormore

`parents’–I.e.generatenewcandidatesolutionsbycombining

bitsandpiecesfromdifferentprevioussolutions.

通过重组将父代优良基因遗传给后代;Morelikeselectivebreedingthannaturalevolution;;;;;;;;;;;;遗传算法的基本思想;;遗传算法历史;遗传算法历史;遗传算法历史;;1.3MajorAdvantages;遗传算法;;;;进化算法遗传算法;1.1IntroductionofGeneticAlgorithms;1.2GeneralStructureofGeneticAlgorithms;1.2GeneralStructureofGeneticAlgorithms;;1.2GeneralStructureofGeneticAlgorithms;1.IntroductionofGeneticAlgorithms;2.ExamplewithSimpleGeneticAlgorithms;2.ExamplewithSimpleGeneticAlgorithms;2.1Representation;2.1Representation;;;;2.2InitialPopulation;;Anevaluationfunctionplaystheroleoftheenvironment,anditrateschromosomesintermsoftheirfitness.(适应度函数起到环境的作用)

Thefitnessfunctionvaluesofabovechromosomesareasfollows:

Itisclearthatchromosomev4isthestrongestoneandthatchromosomev3istheweakestone.;;;1;;;;;;2.ExamplewithSimpleGeneticAlgorithms;2.ExamplewithSimpleGeneticAlgorithms;2.Examp