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Description: To get the Pareto set from a given set of points
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Size: 1753 |
Author: ym |
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Description:
由于演化算法求解多目标优化问题所得结果是一个优化解集———Pareto最优集,而现有的演化算法收
敛性分析只适合针对单目标优化问题的单个最优解。利用有限马尔科夫链给出了演化算法求解多目标优化问
题的收敛性分析框架,并给出了一个分析实例
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Size: 47227 |
Author: fujia |
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Description: 摘
由于演化算法求解多目标优化问题所得结果是一个优化解集———Pareto最优集,而现有的演化算法收
敛性分析只适合针对单目标优化问题的单个最优解。利用有限马尔科夫链给出了演化算法求解多目标优化问
题的收敛性分析框架,并给出了一个分析实例
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Size: 15250 |
Author: fujia |
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Description: 摘
由于演化算法求解多目标优化问题所得结果是一个优化解集———Pareto最优集,而现有的演化算法收
敛性分析只适合针对单目标优化问题的单个最优解。利用有限马尔科夫链给出了演化算法求解多目标优化问
题的收敛性分析框架,并给出了一个分析实例
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Size: 52167 |
Author: fujia |
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Description: 扩展遗传算法SPEAII(Strength Paretor Evaluation Algorithm)算法的代码实现,良好的程序框架，便于向其他应用领域扩展，建议大家使用。-Extended genetic algorithm SPEAII (Strength Paretor Evaluation Algorithm) algorithm code, a good procedural framework to facilitate expansion to other application areas, it is recommended the use of everyone.
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Size: 51200 |
Author: 郭玉华 |
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Description:
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Size: 47104 |
Author: fujia |
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Description: 多目标遗传算法/用法不用多说、要用的赶快下载吧-Multi-objective Genetic Algorithm/usage Needless to say, want to use to download it as soon as possible
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Size: 124928 |
Author: fengtongming |
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Description: 基于生物免疫系统的自适应学习、免疫记忆、抗体多样性及动态平衡维持等功能,提出一种动态多目标免疫
优化算法处理动态多目标优化问题.算法设计中,依据自适应ζ邻域及抗体所处位置设计抗体的亲和力,基于Pa-
reto控制的概念,利用分层选择确定参与进化的抗体,经由克隆扩张及自适应高斯变异,提高群体的平均亲和力,利
用免疫记忆、动态维持和Average linkage聚类方法,设计环境识别规则和记忆池,借助3种不同类型的动态多目标
测试问题,通过与出众的动态环境优化算法比较,数值实验表明所提出算法解决复杂动态多目标优化问题具有较大
潜力.-:A dynamic multi-objective immune optimization algorithm suitable for dynamic multi-objective
optimization problems is proposed based on the functions of adaptive learning, immune memory, antibody
diversity and dynamic balance maintenance, etc. In the design of the algorithm, the scheme of antibody af-
finity was designed based on the locations of adaptive-neighborhood and antibody antibodies participating
in evolution were selected by Pareto dominance. In order to enhance the average affinity of the population,
clonal proliferation and adaptive Gaussian mutation were adopted to evolve excellent antibodies. Further-
more, the average linkage method and several functions of immune memory and dynamic balance mainte-
nance were used to design environmental recognition rules and the memory pool. The proposed algorithm
was compared against several popular multi-objective algorithms by means of three different kinds of dy-
namic multi-objective benchmark problems. Simulations show
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Size: 499712 |
Author: 王飞 |
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Description: 摘 要:提出一种新的基于Pareto多目标进化免疫算法(PMEIA)。算法在每一代进化群体中选取最优非支配抗体保存到记忆细胞文档中 同时引入Parzen窗估计法计算记忆细胞的熵值,根据熵值对记忆细胞文档进行动更新,使算法向着理想Pareto最优边界搜索。此外,算法基于点在目标空间分况进行克隆选择,有利于得到分布较广的Pareto最优边界,且加快了收敛速度。与已有算法相比, PMEIA在收敛性、多样性,以及解的分布性方面都得到很好的提高。-Abstract:This paperproposed a new pareto-based multi-object evolutionary mi mune algorithm(PMEIA). PMEIA selected
optmi alnon-dominated antibodieswhichwere then reserved inmemory cellarchive, and introducedParzenwindow to calculate
entropy ofmemory cells. Updated thememory cell archive according to entropy ofmemory cells. This guarantees the conver-
gence to the true Pareto fron.t Moreover, the performance of clone selection was dependent on distribution in the objective
space, whichwas favorable forgetting awidely spreadPareto frontand mi proving convergence speed. Comparedwith the exis-
ted algorithms, the obtained solutions ofPMEIA havemuch betterperformance in the convergence, diversity and distribution.
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Size: 276480 |
Author: 王飞 |
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Description: 摘要:提出了一种新型的人工免疫算法用来解决多目标函数优化问题。基于自然免疫系统固有的优良特性对算法进行了设计和分析。
最后,算法对3个较复杂的多目标问题进行了优化,优化结果能很好地覆盖问题的Pareto最优面,并且把算法与某些混合遗传算法进行
了对比实验,表明人工免疫算法在解决多目标优化问题上具有可观的研究前景。
-Abstract:In order to effectively solve multiobjective optimization problems, a novel artificial immune algorithm is proposed. It is de
signed and analyzed based on excellent intrinsic features of nature immune systems. Additionally, the algorithm sensitivity to its tuning pa
rameters is briefly assessed. Finally, the algorithm is applied to solve three complex multiobjective optimization problems and the results ca
perfectly map the Pareto-optimal fronts. By comparing the algorithm with some genetic algorithms, it shows the good prospect to apply ar
tificial immune system to solve multiobjective optimization problems.
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Size: 90112 |
Author: 王飞 |
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Description: 利用帕累托最优和协同进化算法做一个模拟，可以应用在多目标优化上。-a simulation using pareto optimization and co-evolutionay algorithm, it could be used to solve multiple objective optimization.
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Size: 10240 |
Author: 刘小宝 |
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Description: 一个非常好用的多目标进化算法，可以轻松的达到PARETO前端-MOEA
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Size: 7168 |
Author: 张锡 |
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Description: 强度PARETO算法，非常经典，也是一个学习多目标进化算法的经典作品。-MOEA
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Size: 210944 |
Author: 张锡 |
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Description:
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Size: 624640 |
Author: 张小三 |
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Description: SPEA2,是一种多目标优化的算法，求可行解集速度比较快！-SPEA2 for multiobjective optimization method， the strength Pareto evolutionary
algorithm2
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Size: 9216 |
Author: yuchenlong |
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Description: 为了有效检测多目标优化进化算法的性能，从3 个方面进行多目标优化测试问题的设计，即约束条件、最优解分布的均匀性、算
法逼近Pareto 最优前沿的难度，采用NSGA-Ⅱ算法对这些测试问题进行仿真实验，并将算法求得的最优解可视化。结果显示，测试问题能够有效检测算法在上述3 方面的性能。-In order to effectively detect the multi-objective optimization evolutionary algorithm performance, from the three aspects of multi-objective optimization test problems of design, that constraint, the uniformity of the optimal solution, Pareto optimal front approximation algorithm of the difficulty of algorithm using NSGA-Ⅱ test questions on these simulations, and obtained the optimal solution algorithm visualization. The results show that the problem can be effectively tested in the above-mentioned three aspects of detection algorithm performance.
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Size: 308224 |
Author: cdong |
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Description: 多目标优化
相对传统多目标优化方法, PSO在求解多目标问题上具有很大优势。首先, PSO的高效搜索能力有利于得到多目标意义下的最优解 其次, PSO通过代表整个解集的种群按内在的并行方式同时搜索多个非劣解,因此容易搜索到多个Pareto 最优解 再则, PSO的通用性使其适合于处理所有类型的目标函数和约束 另外, PSO 很容易与传统方法相结合,进而提出解决特定问题的高效方法。就PSO 本身而言,为了更好地解决多目标优化问题,必须解决全局最优粒子和个体最优粒子的选择问题-Compared with the traditional multi-objective optimization of multi-objective optimization method, PSO in solving multi-objective problem has a great advantage. First, PSO is conducive to the efficient search capabilities are more objective sense of the optimal solution Secondly, PSO representative of the entire solution set through the population by way of the inherent parallel search multiple non-inferior solution, and this can easily search for the most number of Pareto optimal solution Furthermore, PSO' s versatility make it suitable for handling all types of objective function and constraints addition, PSO is easy to integrate with the traditional method, and then propose an efficient way to solve specific problems. The PSO itself, in order to better address the multi-objective optimization problems, the need to address the global best particle and the individual selection of the optimal particle
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Size: 1024 |
Author: 杨科 |
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Description: 一个基于阈值的粒子比较准则，用于处理多目标约束优化问题,该准则可以保留一部分序值较小且约束违反度在允许范围内的不可行解微粒,从而达到由不可行解向可行解进化的目的；一个新的拥挤度函数,使得位于稀疏区域和Pareto前沿边界附近的点有较大的拥挤度函数值,从而被选择上的概率也较大 从而构成解决多目标约束优化问题的混合粒子群算法。-A comparison based on the threshold criteria for the particle to handle multi-objective constrained optimization problem, part of the guidelines can keep order value is small and the constraint violation in allowing infeasible solutions within the particles, so as to achieve a feasible solution to the infeasible solution The purpose of evolution a new function of crowding, making the Pareto front in the sparse region and near the border points have a greater value of the congestion function, which is the larger the probability of selection so as to constitute solve multi-objective constrained optimization problems hybrid particle swarm algorithm.
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Size: 4096 |
Author: 李洪 |
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Description: Interesting article on intuitive n-dimensional Pareto frontier selection.
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Size: 517120 |
Author: Antonio Carlos |
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Description: 基于pareto的多目标遗传算法，它是NSGA2-Pareto-based multi-objective genetic algorithm, which is NSGA2
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Size: 520192 |
Author: luchao |
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