搜索资源列表
MPCYH
- 用于预测控制；单目标优化问题求解；包括非线性约束问题。-For predictive control single-objective optimization problem solving including non-linear constraints.
ABC
- 经典ABC算法求解标准 无约束优化问题 -ABC classical algorithm for solving unconstrained optimization problems
Optimization-correlation
- 1.约束优化问题： minRosen(Rosen梯度法求解约束多维函数的极值)(算法还有bug) minPF(外点罚函数法解线性等式约束) minGeneralPF(外点罚函数法解一般等式约束) minNF(内点罚函数法) minMixFun(混合罚函数法) minJSMixFun(混合罚函数加速法) minFactor(乘子法) minconPS(坐标轮换法)(算法还有bug) minconSimp
GA
- myGA:用基本遗传算法求解一维无约束优化问题 AdapGA:用自适应遗传算法求解一维无约束优化问题-MyGA: Basic genetic algorithm to solve one dimensional unconstrained optimization problem AdapGA: Adaptive genetic algorithm for solving one dimensional unconstra
MOPEAforCOP
- 经典IEEEpaper的代码，进化多目标优化算法求解约束优化问题，值得学习-经典IEEEpaperA multiobjective optimization-based evolutionary algorithm for constrained optimization的代码，值得学习
Midacomo
- MIDACO是一般的优化问题求解器。 MIDACO可应用于连续（NLP），离散/整数（IP）和混合整数（MINLP）的问题。问题可能被限制在平等和/或不等式约束。 MIDACO适合多达数百至几千优化变量的问题。 MIDACO实现了一个自由衍生物，启发式算法的处理方法处理的问题，因为黑盒可含有关键功能特性，如非凸性，不连续或随机噪声。-MIDACO is a solver for general optimization problems
YSPSO
- 一个很有用的带压缩因子粒子群算法的matlab程序，用于求解多维无约束优化问题。-A useful matlab code of particle swarm algorithm with compression factors, it can be used to solve the multidimensional unconstrained optimization problems.
AsyLnCPSO
- 用学习因子异步变化的粒子群优化算法求解无约束优化问题-Using asynchronous learning factor variation of particle swarm optimization algorithm for solving unconstrained optimization problems, are helpful to you!
BreedPSO
- 用基于交叉遗传的粒子群优化算法求解无约束优化问题-Based on cross genetic particle swarm optimization algorithm for solving unconstrained optimization problems, are helpful to you!
CLSPSO
- 用混沌粒子群优化算法求解无约束优化问题,希望对大家有帮助！-Chaotic particle swarm optimization algorithm for solving unconstrained optimization problems, I hope it can help you!
LinWPSO
- 用线性递减权重粒子群优化算法求解无约束优化问题,希望对大家有帮助！-With a linear gradient weight of particle swarm optimization algorithm for solving unconstrained optimization problems, I hope it can help you!
Untitled2
- 利用外点法惩罚函数法求解简单的约束优化问题。可以运行-Outer point penalty function method is used to solve simple constrained optimization problems.
trust-region-method
- 功能：牛顿型信赖域方法求解无约束优化问题min f(x) 输入 x0是初始迭代点 输出：xk是近似极小点，val是近似极小值，k是迭代次数- function: Newton type trust region method for solving unconstrained optimization problem min f (x) input The xo is the initial iteration
AsyLnCPSO
- 用学习因子异步变化的粒子群优化算法求解无约束优化问题-Optimization algorithm uses asynchronous learning factor PSO change unconstrained optimization problems
LinWPSO
- 用学习因子同步变化的粒子群优化算法求解无约束优化问题-Changes in synchronization with the learning factor PSO algorithm for solving constrained optimization problems
SelPSO
- 用基于选择的粒子群优化算法求解无约束优化问题-With selection based on PSO algorithm for solving constrained optimization problems
SimuAPSO
- 用基于模拟退火的粒子群优化算法求解无约束优化问题-With optimization algorithm based on simulated annealing Particle Swarm unconstrained optimization problems
LnCPSO
- 用学习因子同步变化的粒子群优化算法求解无约束优化问题-Changes in synchronization with the learning factor PSO algorithm for solving constrained optimization problems
RandWPSO
- 用随机权重粒子群优化算法求解无约束优化问题-Heavy Particle Swarm Optimization with Random Weight unconstrained optimization problems
PSO
- 基本粒子群优化算法，可快速求解无约束优化问题。-Basic particle swarm optimization algorithm, it can quickly solve unconstrained optimization problems.