NSGA2-MOPSO

利用克拉茂克郎尼变换，求得表面等离子体相位虚数部分再不同波长或入射角度的值(estimation of the imaginary part via Krammers-Kronig relarions)

用麦克麦考方法求解一维burgers方程的matlab代码(By Mike McCaw method for solving one-dimensional burgers equation matlab code)

说明：  多阶段物流配送问题GA解法,用于物流配送中心选址问题的解决(logistics center location)

粘弹正演程序和模型实例,2维数值模拟正演，适应于粘弹介质，(This program can be two-dimensional numerical simulation of acoustic wave equation, Viscoelastic isotropic media.)

牛顿 非牛顿流体数值模拟源代码，对粘弹性流体湍流减阻进行分析(Newton non-Newtonian fluid numerical simulation of the source code, to analyze the viscoelastic fluid turbulent drag reduction)

将txt数据转换为LMS test.lab软件所能接受的格式(Change the txt format file to Unv file which can be read into the famous vibration test software LMS test.lab)

用Fluent VOF模型模拟单个小水滴落入盛水的水杯之中(Fluent VOF model simulations using a single drop falling into a water glass)

说明：  共轭梯度法（Conjugate Gradient）是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(Conjugate gradient method Gradient) is a method between the steepest descent method and Newton's method. It only uses the first derivative information, but overcomes the disadvantage of slow convergence of steepest descent method, and avoids the disadvantage of storing and calculating Hesse matrix and solving inverse of Newton's method. Conjugate gradient method is not only one of the most useful methods to solve large-scale linear equations, but also the most effective method to solve large-scale nonlinear optimization One of the algorithms of. Among all kinds of optimization algorithms, conjugate gradient method is very important. It has the advantages of small storage, step convergence, high stability and no external parameters.)

说明：  运筹学中的运输问题的C++程序，支持产销平衡与产销不平衡，可以判断解的情况。(C++ code of transportation problem)

matlab 实现克里金插值 传统克里金插值 可用于已知少数点的值画整体趋势面(matlab kriging Can be used to draw a few points of the known value of the overall trend surface)