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- Exact Penalty Function and Minimax Problem 精确罚函数和极小极大问题
- An Exact Penalty Function Approach for Linear Bilevel Multiobjective Proramming 二层多目标规划的一个精确罚函数法
- A General Model of Non-Linear Neural Networks Based on Exact Penalty Function 基于精确罚函数的一类广义非线性神经网络模型
- A SMOOTHING APPROXIMATION TO THE EXACT PENALTY FUNCTION FOR OPTIMIZATION WITH INEQULITY CONSTRAINTS 不等式约束最优化的非光滑精确罚函数的一个光滑近似
- The Existence of an Exact Penalty Function Approach for a Class of Two-Level Programming Problems 一类双层规划的恰当罚函数的存在性
- General Exact Penalty Functions in Integer Programming 整数规划中精确罚函数的一般形式
- problem exact penalty function 精确罚函数
- exact penalty function 恰当惩罚函数
- Combined with exact non-differentiable penalty function, a new chaos genetic optimization algorithm is presented. 并结合精确不可微罚函数求解非线性约束优化问题，提出了求解此类问题的混沌遗传算法。
- It is not the Father who exacts penalty . 要惩罚你的，也不是天父。
- It can speed the local rate of convergence and improve the accuracy of solution, and to solve nonlinear constraint optimization problems, COA was combined with exact non-differentiable penalty function. 它利用混沌变量的特定内在随机性和遍历性跳出局部最优点，并在局部搜索空间经过线性搜索提高解的搜索速度和精度，通过结合精确不可微罚函数以用于求解非线性约束优化问题。
- We employan approximated linear search procedure based on the Fletcher exact penalty functionand the use of approximated derivetives of the multiplier function that avoids the needto evaluate the second order derivatives of the problem functions . 并利用Fletcher精确罚函数的近似函数作为线性搜索函数，以避免计算二阶导数。
- Finally, this algorithm is applied to some test problems and it has the better results than using the penalty function algorithm. 最后，本算法应用于几个典型例题，并与罚函数法相比较，数值结果表明该算法是可行的，有效的。
- In this paper, we try to apply Binary System Particle Swarm Optimization (BSPSO) with death Penalty function to solve 0/1 knapsack problem. 摘要将带有死亡罚函数的二进制粒子群优化算法应用于0/1背包问题。
- Penalty function method for solving constrained (minimum) optimization problem of a class of better algorithms. 罚函数方法是求解约束（极小）优化问题的一类较好的算法。
- Furthermore.The theory about penalty function method of bilevel multiobjective programming is established. 在单层化的基础上，建立了两层多目标规划的罚函数理论。
- Firstly, we can convert the constraint LMIP into unconstraint one by using the penalty function. 通过构造一种罚函数化有约束的LMIP为无约束或简单约束的LMIP。
- In the Genetic Algorithm, penalty function is often used to deal with constrains. 摘要在遗传算法中，约束的处理一般采用罚函数法。
- Lastly, PWL predictive control which uses the upper bound of optimal control as penalty function under certain conditions is proved to be stable. 最后证明了在一定条件下将最优控制的上限作为PWL系统预测控制的最终惩罚项可使预测控制算法保持稳定。
- This thesis analyses thecommon penalty function method and modified coulomb friction model used for contactanalysis in sheet metal forming simulation. 分析了常用的罚函数法接触算法和用于板料成形数值模拟的修正库仑摩擦模型。
