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