遺傳算法解決二次函數(shù)問題

學習好資料歡迎下載學習好資料歡迎下載學習好資料歡迎下載<遺傳算法>技術文檔問題：

利用遺傳算法求解區(qū)間[0,

31]上的二次函數(shù)y=x2的最大值

VS2005C++環(huán)境C++面向對象的思想設計遺傳算法各參數(shù)變量的說明（1）shortbitString;//個體的二進制編碼（2）shortfitness;//個體的適應度（3）staticconstshortbitCount=5;//個體二進制碼的長度（4）staticconstshortpopuScale=10;//種群規(guī)模（5）#defineCROSS_MUTATE_PRO_COMP100//交叉、變異的基數(shù)（6）staticconstshortpc=40;//交叉?zhèn)€體數(shù)相對于基數(shù)（7）staticconstshortpm=5;//變異個體數(shù)相對于基數(shù)（8）IndividualpopuArray[popuScale];//種群（9）shortgen=0;//種群進化的代數(shù)遺傳操作的設計思想

分別設計了一個個體類、種群類，種群由個體組成，這是類庫設計，對用戶來說，分別使用這兩個類來實現(xiàn)遺傳算法，其中選擇中采用輪盤賭來選擇下一代。(1)、個體類設計如下：#ifndef__INDIVIDUAL_H__#define__INDIVIDUAL_H__#include<iostream>classIndividual{private: shortbitString;//個體的二進制編碼 shortfitness;//個體的適應度public: staticconstshortbitCount=5;//個體二進制碼的長度 Individual(); Individual(shortn); Individual(shortbitStr,intfit); ~Individual(); shortGetFitness()const; shortGetBitString()const; //voidsetBitString(); //voidsetFitness(); booloperator>(constIndividual&indi)const; booloperator==(constIndividual&indi)const; friendstd::ostream&operator<<(std::ostream&os,constIndividual&indi); voidShowIndividual(void)const;};#endif（2）種群類設計如下：#ifndef__POPULATION_H__#define__POPULATION_H__#include"individual.h"#defineCROSS_MUTATE_PRO_COMP100//交叉、變異的基數(shù)classPopulation{public: staticconstshortpopuScale=10;//種群規(guī)模private: staticconstshortpc=40;//交叉?zhèn)€體數(shù)相對于基數(shù) staticconstshortpm=5;//變異個體數(shù)相對于基數(shù) IndividualpopuArray[popuScale];public: Population(); voidSelection();//選擇 voidCrossover();//交叉 voidMutation();//變異 constIndividual&GetbestIndividual()const; constIndividual&GetRepresatationIndividual()const; friendstd::ostream&operator<<(std::ostream&os,constPopulation&p); voidShowPopulation()const; ~Population();};#endif（3）用戶區(qū)程序代碼（遺傳算法實現(xiàn)）：#include<iostream>#include"individual.h"#include"population.h"voidGA(void);intmain(){ GA();}voidGA(void){ std::cout<<"Pleaseenterhowmanygenerationsyouwantthepopulationtoevolve!"<<std::endl; shortgen=0;//種群進化的代數(shù) std::cin>>gen; Populationbirds; for(inti=0;i<gen;i++) { std::cout<<"the"<<i<<"thgeneration:"<<std::endl; std::cout<<birds<<std::endl; birds.Selection(); std::cout<<"afterselectionthepopulationis:"<<std::endl; std::cout<<birds<<std::endl; birds.Crossover(); std::cout<<"aftercrossoverthepopulationis:"<<std::endl; std::cout<<birds<<std::endl; birds.Mutation(); std::cout<<"aftermutationthepopulationis:"<<std::endl; std::cout<<birds<<std::endl; std::cout<<std::endl<<std::endl; } std::cout<<"After"<<gen<<"evolutionthebestfitnessIndividualbirdis:"<<std::endl; std::cout<<birds.GetbestIndividual()<<std::endl; std::cout<<"After"<<gen<<"evolutiontherepresetationalIndividualbirdis:"<<std::endl; std::cout<<birds.GetRepresatationIndividual()<<std::endl;}程序流程圖

開始開始Gen=0編碼隨機產(chǎn)生N個初始個體滿足終止條件?計算群體中各個體適應度從左至右依次執(zhí)行遺傳算子j=0j=0j=0根據(jù)適應度選擇復制個體選擇兩個交叉?zhèn)€體選擇個體變異點執(zhí)行變異執(zhí)行交叉執(zhí)行復制將復制的個體添入新群體中將交叉后的兩個新個體添入新群體中將變異后