分别分析了两种模式下的决策过程，进行了优化求解。
The decision processes in two modes were analyzed and the optimal solutions were found.
对建立的计算模型采用序列二次规划法进行优化求解。
The objective functions are obtained by use of the sequential quadratic programming.
对形成的非线性数学模型，采用遗传算法进行优化求解。
GA is used to optimize the indexes of the formed nonlinear mathematical model.
通过优化求解，获得了比较理想的送布轨迹，解决了行业内的难题。
Using optimum technique the idealer conclusion which solved the problem in trades is obtained.
针对主从递阶决策问题的优化求解，提出基于回溯算法的优化方法。
An optimal method based on the back-tracing algorithm is presented for calculating the entire system restoration plan.
经实际运行证明，这是一条简单可行，易于推广的最优化求解途径。
It is indicated by the practical example that this approach is a simp1e and significant solution for proportional optimization design.
分别分析了两种补偿成本结构下的供应链收益函数，进行了优化求解。
The profit functions of supply chain in two compensation cost structure are analyzed and the optimal solution is found.
并以成都地铁作为案例运用MATLAB进行大轴承主参数优化求解。
Chengdu metro is as the case of solving the optimization problem by MATLAB.
提出一种电容射频热疗中优化求解预期深部有效热区分布逆问题的方法。
An inverse optimization method, applied in hyperthermia to search the ideal heating physical configurations in the expected temperature distribution of heat-field, was proposed.
介绍了数据包络分析方法及其非线性模型，并提出了混沌优化求解算法。
Data envelopment analysis (DEA) and its non-linear model are introduced, and chaos optimization algorithm is used to find the non-linear model.
引入改进模拟退火算法进行全局最优化求解方程，并给出程序编制流程图。
Using the improved annealing simulation algorithm, full, scale solution of optimal equation is obtained with flow chart for programming.
结合数字信号处理技术以及数值分析方法，解决了结构优化求解规模巨大的难点。
For decreasing the computational scale, adjoint variable method is proposed to solve the sensitivity analysis based on FEM.
运用基于实码的加速遗传算法(RAGA)优化求解了春小麦作物水模型的敏感系数。
The sensitive indexes of crop water model for spring wheat has been get with RAGA.
总结和归纳了计及不确定因素的电网灵活规划方法，并对各种优化求解算法进行了综述。
The methods of transmission network flexible planning considering the uncertainties are summarized and concluded, and kinds of the optimization algorithm are reviewed.
最后基于非线性最小二乘法对模型进行优化求解，得出了SR重建图像及其全局运动域。
Nonlinear least squares method is employed to solve the model to get the global motion area of SR resolution.
该方法利用最大似然准则建立目标函数，同时利用非线性共轭梯度法来优化求解目标函数。
The objective function was established based on the maximum likelihood rule, which was solved by nonlinear conjugate gradient method.
它的主要步骤是：预测出水运需求量，建立运力运量平衡模型，在用计算机进行优化求解。
The main procedure is predicting the demand of waterway transport by establishing balance model of transport ability and quantity in computer.
圆度的评定和计算，实质上是根据圆度的定义构造函数模型、再进行函数优化求解的过程。
The assessment and calculation for roundness essentially is the process in which the functional model is constructed and optimally solved according to the definition of roundness.
最小能量的优化求解用迭代条件模式(ICM)方法，初始分割标记场用矢量直方图法得到。
The optimization of solution is carried out by Iterated Conditional Mode (ICM) method. The initial segmentation label fields is gotten using vector histogram.
给出了角点检测算法、退化问题的避免措施以及基于秩2约束的基础矩阵迭代优化求解的方法。
The corner detection algorithm, avoidance of the degeneration problem and the fundamental matrix iterative optimization algorithm based on rank-2 constraint were introduced.
在随机预测控制中，约束是机会约束，目标函数是数学期望，滚动优化求解的是随机优化问题。
In Stochastic Model Predictive Control, chance constraints are presented and the objective function is an mathematical expectation.
同时，引入变量代换，基于线性规划的单纯形法，提出该类绝对值规划问题的全局优化求解算法。
Based on variable substitution and the simplex method for linear programming, the paper also discusses the global optimization algorithm for the absolute value programming.
设计了一种采用基于编号的整数编码方案的简单通用协同进化算法，实现了对重构模型的优化求解。
A simple universal coevolutionary algorithm based on pointer-based integer coding schema is implemented to find the optimal solution of the reconfiguration model.
结合混沌变量的随机遍历特性，将混沌优化算法应用于输电网非线性混合整数规划模型的优化求解。
Given the stochastic and ergodic characteristics of fuzzy variables, a chaos optimization algorithm is introduced to solve the planning problem.
为此，根据企业利润最大化原则建立机组经济运行数学模型，并用改进粒子群算法对模型优化求解。
In this paper, based on the principle of maximum profit, a mathematical model of unit which is unit economy operation is presented.
该算法将非线性搜索转化为只对当前控制增量的约束，避免了非线性优化求解，并不需要很多的计算量。
The algorithm converts the nonlinear searching into the constraint on present control increment and avoids the complicated nonlinear optimization. The computation burden is not very serious.
结果表明对于数据量庞大的非线性模型的优化求解，改进后的进化规划算法具有更强和更广泛的适用性。
The result shows that improved evolutionary programming is much more appropriate of none line model with a great volume of data.
结果表明对于数据量庞大的非线性模型的优化求解，改进后的进化规划算法具有更强和更广泛的适用性。
The result shows that improved evolutionary programming is much more appropriate of none line model with a great volume of data.
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