Announcing LINGO 20 : New Features
+ Improved API interface. It is now much easier to incorporate your LINGO
model(s) into your own custom designed system.
The standard LINGO distribution has examples to illustrate how to do this.
+ LINGO in Excel. It is now easy to integrate a LINGO model into an Excel
spreadsheet. The end user sees it as just a smart Excel spreadsheet that can solve say,
a cutting stock problem for metal fabrication, or vehicle routing and delivery problems, or
a supply chain shipping assignment problem, and more.
+ New REST API distributed computing interface. If you want to have an
optimization based application accessible on the web from smart phones and
other devices, this is now easier to do.
+ Improved capability to create a Docker Image. If you like to be able to move an
application from one server to another with minimum hassle, Docker has proven to
be a popular way of achieving such portability.
+ Improved interface to R. The R statistical package is a popular way of doing
statistical analysis. It is now much easier to establish an interface between your
data in R and your optimization model in LINGO.
+ Improved interface to Python. Python is one of the most popular languages for
doing general computations. It is now much easier to establish an interface
between your Python application and your optimization model in LINGO.
+ Improved support for implied set names such as J01..J99, Jan..Oct, etc.
+ Improved ODBC connection to databases allowing import of sets (in addition to
attributes) within Calc sections.
+ Ability to generate alternate optimal solutions to linear programming models.
This may be done interactively, or programmatically within Calc sections using the
@NEXTALTOPT() function.
Performance Improvements
+ Linear and Integer Solver Improvements.
Improved heuristics for general integer programs.
Average performance improvement of 2-3% on our standard test set.
+ Nonlinear and Global Solver Improvements
Faster (order of magnitude) solution of linear fractional programs (ratio
objectives)
+ Support for additional useful but “problematic” functions:
Power utility function (x^g-1)/g and
exponential ratio function (exp(g) – 1)/g, are important in some
situations modeling consumer behavior. The solver can now robustly avoid the
numerical problems that would otherwise occur when g approaches 0.
+ Linearization Improvements
More expressions can be automatically linearized, so you can now use a fast
linear solver where otherwise a much slower (30x?) nonlinear solver might be
required. Improved linearization of certain IF expressions.
