LINGO 17 includes a wide range of performance enhancements and new features.

 

Faster Solutions on Linear Models with Improved Simplex Solver

Enhancements to the Simplex solvers boost performance on linear models. Large models solve an average of 20% faster using primal simplex and 15% faster for dual simplex.

 

Improved Integer Solver

New symmetry detection capabilities dramatically reduce the time required to prove optimality on certain classes of models with integer variables. Performance has been improved on Markowitz portfolio problems with minimum buy quantities, and/or limit on number of instruments at nonzero level. Other enhancements provide faster solutions on certain task assignment-like models.

 

Global Solver Enhancements

Stability and robustness of the Global solver has been improved through several enhancements to quadratic recognition and range reduction. Improved exploitation of convexity of certain ratio constraints, e.g., as found in heat exchanger network design problems.

 

More Constraint Types Supported

Several new functions and constraint types are recognized, e.g., the @AllDiff constraint for general integer variables. The @AllDiff function allows one to specify a set of integer variables, such that each variable in the set must have a unique value, different from all other variables in the set.

 

Most Recent Modeling Language and Feature Enhancements

•             New capability to pass arguments to user-defined procedures.

•             Support of data frame style input in Data and Calc sections has been added.

•             New functions for programmatically reading input data in Calc sections.

•             New function for retrieving the next best solution to a binary integer programming model. The function allows you to examine and/or display variable values and decide if further solutions should be generated, or it can be called repeatedly to iterate through all feasible solutions.

•             New function for displaying space time charts.

•             New functions for performing QR factorization of matrices and performing matrix multiplication.

•             Option for specifying the default starting point for variables.