LINGO 16的發布包含了一系列性能提升和新功能
功能升級的Simplex求解器使線性模型擁有更快的處理速度。Simplex求解器性能的增強提升了大型線性模型的性能。處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%。
整數求解器的新功能
引入了一個新的優化模式確保運行的再現性?？焖僬业阶顑炋娲桨?，增強的K-Best算法可以很快的找到多個最佳的K解決方案，而不只一個解決方案。使用新的啟發式算法可快速找到knapsack約束和塊結構模型的解決方案。新的預處理級別收緊變量邊界來更好的實現非線性模型的性能。
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.
隨機求解器功能增強
使用改進的切割管理，嵌套Benders分解法的大型線性多級SP實例求解速度提高60%。
通過改善Nested Benders Decomposition Method的切割管理來提高大型線性多級SP實例60%的速度。
更好的處理多級不完整的SP模型。
解析器的擴展允許使用任意復雜隨機參數的函數。
Improved Global Solver 改進的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求解器在二次問題的性能已經得到了極大的提升。尤其是其他求解器解決不了或是處理的很慢的non-convex quadratic問題，還可以解決一些之前特別棘手的問題，尤其是最小購買數量的金融投資組合模型，以及在非零水平下限制數量的儀器。
還包含了一個新的壓縮過程的線性化進程，提高了線性模型的可解性。
在許多模型上有了顯著的提速和性能增強，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系統支持
LINGO的用戶界面已經完全的重寫用來適應Mac和Linux系統。
以下是在MAC版本下運行小的非線性程序的示意圖。
Matrix Functions: 矩陣功能
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中加入了一系列用來執行矩陣操作的新功能。
支持的操作包括：特征值和特征向量的計算，矩陣行列式，丘拉斯基分解，反矩陣以及矩陣轉置
Linear Regression: 線性回歸
The new @REGRESS function for multiple linear regression has been added.
添加了新的回歸函數用來處理多元線性回歸。
Other Improvements: 其它改進
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圖表。
新增了排序功能，為數據準備和解決方案報告提供便利。
新的日期功能@STM2YMDHMS，可以將LINGO的標準時間參數轉換為等同的日歷日期和時間。
