Implementation requires header only C++ linear algebra library Eigen (https://eigen.tuxfamily.org/) and C++ standard 20+.

Currently Derivative-free method particle swarm optimization (PSO) and Nelder-Mead Method is implemented.

Algorithm will try to find the global minimum of C function f with signature:

double f(double*)

where double* is a C double array / pointer to input vector (f64 array)

the argument int d in the algorithm is the dimension of input vector, the behavior of program is undefined if d is provided with wrong value.

argmin of objective function will be returned as std::vector<double>

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编译需要C++线性代数库Eigen(https://eigen.tuxfamily.org/) 和C++标准20+。

目前仅简单实现了粒子群优化与Nelder-Mead单纯形算法。

算法将试图找到具有以下签名的C语言函数 f 的全局最小值。

double f(double*)。

其中double*是一个C数组/指向 f64 输入向量数组的指针

算法中的参数int d是输入向量的维度。 如果d提供了错误的值,程序的行为将无法定义。

目标函数的argmin将以std::vector<double>的形式返回。

编译粒子群算法需要链接openmp,因只使用了并行for循环,若不需要可直接移除,并设置rand的tid为0即可。

• C++实现particleswarm
• C++实现matlab优化函数fminsearch (before Feb 5); https://ww2.mathworks.cn/help/matlab/ref/fminsearch.html
• 添加文档,算法可视化; Add docs and visualization
• implement some quasi-Newton methods: Limited-memory BFGS, Newton-cg