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nsga2_Matlab_xixilee
- 对多目标优化算法NSGA-II算法的改进,该算法进化代数少,但是获得的最终效果特别好!-pair of multi-objective optimization algorithm NSGA-II algorithm, the algorithm evolutionary less algebra, However, the ultimate effect was particularly good!
NSGA-II
- NSGA-II源程序,用于求解多目标优化问题,是对NSGA在非支配集构造方法,维持解分布性策略等方面进行的改进。-NSGA-II source code for multi-objective optimization problem, NSGA is a non-dominated set in the constructor, maintenance solutions and other aspects of the distribution strategy of improvement
NSGA2-dynamic
- 多目标优化进化算法目前公认效果收敛性最好的算法NSGA2c++源码,具有一般性,可在此基础上继续改进,对实现其他多目标优化算法很有帮助.-Multi-objective optimization evolutionary algorithm is currently the best recognized effect of convergence of the algorithm NSGA2c++ Source, with the general, could be on this basis
Advance-NSGA-II
- 改进的NSGA-II的简单例子,包含NSGA-II的基本思想,直接在matlab中就可以运行。-Improve the NSGA- II simple examples, including the NSGA- II, the basic idea of directly can run in matlab.
INSGA-II
- 针对NSGA-II算法存在重复个体的问题进行改进INSGA--Improvements INSGA-II for the NSGA-II algorithm duplicate individual problems
毕业论文《NSGA—II的改进算法研究》
- 是一个对多目标遗传算法进行改进的硕士论文,比较有价值。(It is a master's thesis to improve the multiobjective genetic algorithm, which is of great value.)
NSGA
- 多目标遗传算法是NSGA-II[1](改进的非支配排序算法),该遗传算法相比于其它的多目标遗传算法有如下优点:传统的非支配排序算法的复杂度为 ,而NSGA-II的复杂度为 ,其中M为目标函数的个数,N为种群中的个体数。引进精英策略,保证某些优良的种群个体在进化过程中不会被丢弃,从而提高了优化结果的精度。采用拥挤度和拥挤度比较算子,不但克服了NSGA中需要人为指定共享参数的缺陷,而且将其作为种群中个体间的比较标准,使得准Pareto域中的个体能均匀地扩展到整个Pareto域,保证了种群的多样性