自60年代以来，人们对求解多目标优化问题的兴趣日益增加。
Since the 60s, people's interest on solving the multi-objective optimization questions has increased day by day.
它的潜在并行性及自组织、自适应、自学习的智能特性对于求解多目标优化问题具有巨大的潜力。
Due to its intrinsic parallelism, self-organizing, adaptation and self-learning intelligent properties, evolutionary computation has large potential to solve multiple objectives optimal solutions.
计算机仿真表明，该算法可以明显改善求解多目标优化问题时的寻优过程，能适应实际应用环境下快速、有效的决策要求。
The simulation results demonstrate that the new algorithm can improve the process of MOP optimization, and can meet the requirements of high-speed and effectiveness in application.
通过对多目标优化方法研究现状的分析，针对多目标优化问题的特点提出一种基于联合正态分布的求解多目标优化问题的分布估计算法。
By analyzing the research status of Multi-Objective optimization, an Estimation of distribution Algorithm for Multi-Objective Problem based on joint normal distribution is proposed.
针对科学和工程研究中的病态逆问题，提出了基于多目标优化的求解方法。
The resolution strategy for ill-posed inverse problems encountered in science and engineering researches is put forward, based on multi-objective optimization.
通过对各目标实现程度的隶属函数进行定义，将多目标优化问题转变成模糊规划问题进行求解。
By defining the membership function of the realization extent of each objective, the multi-objective optimization problem has been turned into a fuzzy programming problem to be solved.
对离散变量的析架尺寸优化问题，本文提出了采用多目标规划的思想、将离散变量优化和连续变量优化结合起来的求解方法。
In sizing optimization of truss with discrete variables, joined up optimization of continuous variable and discrete variable, the idea of multi-objections is used.
引进了求解一类多目标优化问题弱有效解的优界数列方法，给出了这种优界数列的构造法及相应的算法。
An optimal boundary sequence method is introduced to find the weak efficient solution to a multi objective optimization problem.
多目标过程优化综合问题为多目标混合整数非线性规划模型的求解。
This question almost solves the model of Multi-objectives Mix-integer Nonlinear Programming (MOMINLP).
因此，多目标优化问题的求解变得困难。
So it is much more difficult to solve the multi-objectives optimization problems.
通过实例仿真，结果表明本文的多目标粒子群算法求解半导体生产计划及能力计划多目标优化问题是可行的。
Through the example simulation, the result indicated that MOPSO in this paper works well to solve the problem of production planning and capacity planning of semiconductor.
然后，利用线性加权法和主要目标法将多目标优化问题转化为单目标优化问题，采用精确算法思想进行模型求解。
Then it USES linear weighting method and main target method to convert the problem of multi-objective optimization into a mono-objective one and works out its solution via exact algorithm.
提出了基于场景的多目标随机规划模型来构建不确定市场需求环境下的能力计划问题模型，并用改进的多目标粒子群优化算法求解。
We formulated scenario based multi-objective stochastic programming model to describe the problem of capacity planning under uncertainty and applied improved Multi-Objective PSO (MOPSO) to solve it.
提出了基于场景的多目标随机规划模型来构建不确定市场需求环境下的能力计划问题模型，并用改进的多目标粒子群优化算法求解。
We formulated scenario based multi-objective stochastic programming model to describe the problem of capacity planning under uncertainty and applied improved Multi-Objective PSO (MOPSO) to solve it.
应用推荐