LINGO 16的发布包含了一系列性能提升和新功能
功能升级的Simplex求解器使线性模型拥有更快的处理速度。Simplex求解器性能的增强提升了大型线性模型的性能。处理大型模型的速度比使用primal simplex平均提升了35%比dual simplex提升了20%。
整数求解器的新功能
引入了一个新的优化模式确保运行的再现性。快速找到最优替代方案，增强的K-Best算法可以很快的找到多个最佳的K解决方案，而不只一个解决方案。使用新的启发式算法可快速找到knapsack约束和块结构模型的解决方案。新的预处理级别收紧变量边界来更好的实现非线性模型的性能。
Better handling of multistage SP models which do not have full-recourse.
Extensions to the parser allow the use of arbitrarily complex functions of stochastic parameters.
随机求解器功能增强
使用改进的切割管理，嵌套Benders分解法的大型线性多级SP实例求解速度提高60%。
通过改善Nested Benders Decomposition Method的切割管理来提高大型线性多级SP实例60%的速度。
更好的处理多级不完整的SP模型。
解析器的扩展允许使用任意复杂随机参数的函数。
Improved Global Solver 改进的Global求解器
Performance of Global solver has been dramatically improved on classes of quadratic problems. In particular, non-convex quadratic problems rejected by other solvers, or otherwise solvable only slowly to a local optimum by traditional NLP solvers. Can solve some previously intractable problems to global optimality, especially financial portfolio models with minimum buy quantities,and/or limit on number of instruments at nonzero level.
Incorporates a new bound tightening process to the linearization procedure and improves solvability of linearized model.
Dramatically faster, more robust performance on many models with functions like @MAX( ), @MIN( ), @ABS( ), x*z where z = 0 or 1, etc.
Global求解器在二次问题的性能已经得到了极大的提升。尤其是其他求解器解决不了或是处理的很慢的non-convex quadratic问题，还可以解决一些之前特别棘手的问题，尤其是最小购买数量的金融投资组合模型，以及在非零水平下限制数量的仪器。
还包含了一个新的压缩过程的线性化进程，提高了线性模型的可解性。
在许多模型上有了显著的提速和性能增强，如@MAX( ), @MIN( ), @ABS( ), x*z where z = 0 or 1等等。
Native Macintosh and Linux Support
LINGO's user interface has been entirely rewritten to offer native support for the Macintosh and Linux platforms.
Below is an image of the Mac version running a small nonlinear program.
本地Mac和Linux系统支持
LINGO的用户界面已经完全的重写用来适应Mac和Linux系统。
以下是在MAC版本下运行小的非线性程序的示意图。
Matrix Functions: 矩阵功能
There have been a number of new functions were added to LINGO for performing matrix operations.
Supported operations include: eigenvalues and eigenvector computation, matrix determinant, Cholesky factorization,matrix inverse, and matrix transpose.
LINGO中加入了一系列用来执行矩阵操作的新功能。
支持的操作包括：特征值和特征向量的计算，矩阵行列式，丘拉斯基分解，反矩阵以及矩阵转置
Linear Regression: 线性回归
The new @REGRESS function for multiple linear regression has been added.
添加了新的回归函数用来处理多元线性回归。
Other Improvements: 其它改进
Tornado charts now supported.
Additional sorting capabilities, convenient for data preparation and solution reporting.
A new date function, @STM2YMDHMS, for converting LINGO's standard time values into the equivalent calendar date and time.
支持Tornado图表。
新增了排序功能，为数据准备和解决方案报告提供便利。
新的日期功能@STM2YMDHMS，可以将LINGO的标准时间参数转换为等同的日历日期和时间。
