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采用了保优的选择遗传算法
终止条件的判断是：到达一定的代数。可改进为：相邻若干代的种群平均适应值的变化来判断。若相邻若干代的种群平均适应值为变化或者是变化小于某一阈值，表示算法已经收敛，则退出算法。
选择算子：轮盘赌选择；
交叉算子：单点交叉,随机选择计算此适应度值，若大于当前最佳适应度值则降低交叉概率，否则不变；
变异算子：模板,对于优势个体，除采用低概率变异外，变异位置应采取权值越大，变异概率越小的原则,而对劣势个体则相反.,Paul used the choice of excel
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此代码是实数编码遗传算法的Matlab例程。用了精英保留策略选择和轮盘赌选择法，叉操作采用中间重组方式。-This code is a real-coded genetic algorithm Matlab routines. Retention policies with the elite selection and roulette wheel selection method, fork operation mode using the middle of restructuring.
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fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作-fga.m the main program for the genetic algorithm using binary Gray encoding, roulette wheel based on the law of non-linear ranking selection, uniform crossover and mutation operation
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遗传算法程序说明: fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Descr iption of the procedures for genetic algorithms: fga.m main program for the genetic algorithm using binary Gray encoding, roulette wheel based on the law of non-line
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fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-fga.m the main program for the genetic algorithm using binary Gray encoding, roulette wheel based on the law of non-linear ranking selection, uniform crossover and mutation operati
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fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-fga.m the main program for the genetic algorithm binary Gray encoding, roulette wheel method based on non-linear ranking selection, uniform crossover and mutation operations, but al
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遗传算法求解TSP问题源代码，简单明了，采用轮盘赌进行遗传选择-TSP problem genetic algorithm source code is simple, using the genetic roulette wheel selection
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说明: fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Descr iption: fga.m genetic algorithm for the main program binary Gray encoding, roulette wheel method based on linear ranking selection, uniform crossover and mutation operator
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说明: fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Descr iption: fga.m genetic algorithm for the main program binary Gray encoding, roulette wheel method based on linear ranking selection, uniform crossover and mutation operato
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说明: fga.m 为遗传算法的主程序 采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Descr iption: fga.m genetic algorithm for the main program binary Gray encoding, roulette wheel method based on linear ranking selection, uniform crossover and mutation operato
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遗传算法求函数最值问题 matlab代码 使用轮盘赌选择 交叉 变异-Genetic algorithm for function most value problem matlab code crossover and mutation using the roulette wheel selection
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遗传算法求解TSP问题，采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Genetic algorithm for solving TSP problem, using the binary Gray code, based on the roulette wheel method of non-linear ranking selection, uniform crossover, mutation, but also introduce
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binary genetic algorithm and all its functions such as cross over, mutation, roulette wheel selection and tournament selection included
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遗传算法
编码解码采用二进制编解码
交叉
变异
选择操作采用轮盘赌
-genetic algorithm
The binary coding and decoding decoding
Crossover
Mutation
The roulette wheel selection operation
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遗传算法最优保留 轮盘赌选择、单点交叉、位点变异 绘制最优适应度进化曲线-Genetic algorithm for optimal retention roulette wheel selection, single point crossover Loci draw optimal fitness evolution curve
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用改进遗传算法求解TSP问题,并编制了完整的Matlab程序予以仿真实现.程序中选择算子采用最佳个体保存与赌轮选择相结合的策略,最后分析了最佳个体保存比例对寻优效果的影响. 更多还原-Improved genetic algorithm for TSP, and the preparation of a complete Matlab simulation program to be achieved. Program, select the operator uses the best in
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人工智能方面 利用遗传算法解决一阶函数优化求解,运用了轮赌盘选择，单点交叉等算法-Artificial intelligence using genetic algorithms to solve a first order function optimization solution, using a round roulette wheel selection, single-point crossover algorithms
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