多目标优化问题,multi-objective optimization problem
1)multi-objective optimization problem多目标优化问题
1.A Framework for Multi-objective Optimization Problem Solving多目标优化问题的求解框架
2.In the mid-1980s, Evolutionary Algorithm was introduced to solve the Multi-objective Optimization Problem.在20世纪80年代中期,进化算法开始应用于解决多目标优化问题。
3.Themulti-objective optimization problem based on pareto is a important research direction of the evolutionary algorithm,and how to improve the efficiency of constructing the Pareto non-dominated set is a key to the algorithm.基于Pareto的多目标优化问题是进化算法的一个重要研究方向,而如何构造Pareto非支配集则是提高算法效率的关键所在。
英文短句/例句
1.Particle swarm optimization for multi-objective programming problems求多目标优化问题的粒子群优化算法
2.Proposal of Hybrid Optimization Algorithm for Solving Multi-objective Optimization Problems一种多目标优化问题的混合优化算法
3.Effective Pareto Optimal Set of Multi-Objective Optimization Problems多目标优化问题的有效Pareto最优集
4.New Evolutionary Algorithms for Multiobjective Optimization Problems;解决多目标优化问题的几种进化算法
5.Research on Differential Evolution Algorithm for MOPs多目标优化问题的差分进化算法研究
6.Evolutionary Algorithms for Single-Objective and Multi-Objective Optimization Problems解决单目标和多目标优化问题的进化算法
7.AN ORDINAL ALGORITHM FOR MULTI-OBJECTIVE OPTIMIZATION;一个求解多目标优化问题的排序算法
8.Multi-objective Optimization of One Kind of Generalized Type Ⅰ Function一类广义Type Ⅰ函数的多目标优化问题
9.The Optimality of Multiobjective Programming with S-Subdifferential FunctionsS-次可微下多目标优化问题的最优性条件
10.The Primarily Study of Calculation Method of Multi-aim Optimization Problem in Chemistry Test化学试验中多目标优化问题计算方法的初探
11.An Improved Evolutionary Programming for Multiobjective Optimization;一种解决多目标优化问题改进的进化规划算法
12.The Research on Differential Evolution Algorithm for Solving Multi-Objective Optimization Problem解决多目标优化问题的差分进化算法研究
13.Quantum-inspired immune evolutionary algorithm with classified mutation for solving multi-objective optimization problems求解多目标优化问题的分级变异量子进化算法
14.Linear Evolutionary Algorithm for Constrained Multi-objective Optimization Problems一种求解约束多目标优化问题的线性进化算法
15.The Modified PSO Algorithm and Its Application in Multi-objective Optimization Problem;改进微粒群算法在多目标优化问题中的应用
16.The Research on Particle Swarm Optimization Algorithm to Solve Multi-Objective Optimization Problem;解决多目标优化问题的粒子群算法研究
17.The Particle Swarm Optimization s Amelioration of Transacting Multi-objective Optimization Problem and Its Application;求解多目标优化问题的粒子群算法改进及应用
18.Solving Multi-objective Problem Base on QPSO Algorithm;基于QPSO算法求解多目标优化问题及其应用
相关短句/例句
multi-objective optimal problem多目标优化问题
1.The new representation proposed in this paper deals with the partitional clustering problem by regarding it as amulti-objective optimal problem;in this approach the niche Pareto genetic algorithm is used to solve the problem.为了解决该问题,提出将产状数据的划分问题转化为多目标优化问题,并采用小生境Pareto遗传算法进行求解。
2.This paper introduce a new and efficient multi-objective evolutionary algorithms (EMOEA) for solving unconstrained and constrainedmulti-objective optimal problems (MOPs).利用 Better函数对多目标优化问题 (MOP)建立了一种偏序关系 ,并通过这种偏序关系对种群中的个体进行排名 ,设计了一种高效的多目标演化算法 (EMOEA) ,应用有限 Markov链的有关理论证明了此演化算法的收敛性 ,同时对四个 Benchmark函数进行了数值试验 ,测试结果表明 ,新算法在解集分布的均匀性、多样性、精确性以及快速收敛性均优于已有的 MOEA。
3)multi-objective optimization多目标优化问题
1.Novelε-dominance multi-objective evolutionary algorithms for solving DRSmulti-objective optimization problems;求解DRS多目标优化问题的新颖ε-支配进化算法
2.Genetic algorithms based on colony searching are especially suitable for solvingmulti-objective optimization problems.基于群体搜索的遗传算法求解多目标优化问题具有独特的优势,鉴于决策者事先对于各目标的重要性一般只有模糊的认识,文中对各目标进行了模糊化处理,构造了适应值函数,提出了基于模糊逻辑的多目标优化问题遗传算法求解方案。
3.The algorithms which employ this crossover operator behave very well when they are used to solve Multi-objective Optimization Problem and , to a certain extent, solve the puzzle, i.针对实数编码遗传算法提出了一种通用的基于决策变量的复合交叉算子,并将之用于多目标优化问题的求解,算法效果良好,一定程度上解决了高维多目标优化问题在用遗传算法求解时收敛性差这一难题。
4)multiobjective optimization problem多目标优化问题
1.Used the idea and the selection mechanism called replicator dynamics of evolutionary game theory for reference, and proposed an evolutionary game based optimization algorithm (EGOA) to solvemultiobjective optimization problems (MOPs).为了对算法性能进行评估,采用了一组多目标优化问题(MOPs)的测试函数进行实验。
5)multiobjective optimization problems多目标优化问题
1.Interval slope methods for class ofmultiobjective optimization problems一类多目标优化问题的区间斜率法
2.Interval algorithm of constrainedmultiobjective optimization problems一类带约束多目标优化问题的区间算法
6)multiobjective optimization problems多目标最优化问题
1.In this paper,we define rationality function formultiobjective optimization problems and prove that most of themultiobjective optimization problems are structurally stable and robust.本文对多目标最优化问题定义了理性函数,证明了大多数的多目标最优化问题都是结构稳定和鲁棒的。
延伸阅读
军事问题决策优化军事问题决策优化optimization of military decision makinglunshi wenti iuece youhua军事问题决策优化(op‘imiZation ofmizita叮deeision making)定量描述军事决策问题，寻求最优解或满意解的方法和活动。其目的是为军事问题的决策提供定量依据。常用的理论和方法有数学规划、排队论、对策论和网络分析等。军事问题决策优化，要求把需要决策的军事问题抽象成既反映军事行动(或作业)的最本质特征，又符合运筹学理论所要求的结构的数学模型。军事问题决策优化模型的基本要素是作业、决策方案和效能准则。作业是为达到一定军事目的而采取的运用资源(人力、物力、则一力、时间等)的行动。决策方案是待选的某种作业方案或某些表示作业方案特征的参数。效能谁则是用以评价作业成效的数量指标。例如:线性规划要求的数学模型是以一组决策变量表示作业方案，这些变量应满足以一组线性方程或线性不等式表示的约束条件，优化的目标函数应是决策变量的线性组合。优化问题的一般提法是:在限定的作业条件卜，寻求使效能准则达到最大值或最小值的决策。例如，对作战行动方案的优化，可以是以最少的兵力、兵器达到一定的作战目的;也可以是以一定的兵力、兵器达到最大的作战效果。在前一种提法下，效能准则可取为完成任务所需兵力、兵器数量的数学期望值;在后一种提法下，效能准则可取为完成战斗任务的概率或目标毁伤数的数学期望值。当作.线行动复杂时，还可取多个准则进行优化。应用优化理论寻求军事问题决策优化方案的局限性在于:①最优性只是就某一给定准则而言的，实际军事问题决策优化的准则往往有多个，各准则间可能有不同的量纲或相互矛盾的要求，某些准则甚至不能量化。②要求建立符合某种特定结构的数学模型，而实际军事问题的决策优化往往不能用具有这种特定结构的模型来充分刻画。③问题的解是确定的，但实际军事问题中的许多不确定因素难以都考虑到。由干上述原因，许多决策问题常常不可能或不需要找到最优解，而只需求出满意解。寻找满意解一般可借助于系统模拟、决策分析、专家系统等方法。(怅最良)
