Callable Solver for Application Developers


Quadratic Support and Analyzation Tools Added

The LINDO API Release 1.1 includes a number of enhancements including quadratic optimization capabilities and powerful tools for analyzing infeasible and unbounded models.


Solve Quadratic and Quadratically Constrained Models

In addition to solving linear and mixed integer models, LINDO API can solve models in which the objective function and/or some constraints include quadratic terms. LINDO API can even handle quadratic models with binary and general integer restrictions. These quadratic capabilities make LINDO API suitable for applications such as portfolio optimization problems, constrained regression problems, and certain classes of difficult logistics problems (layout problems, fixed-charge-network problems with quadratic objectives).


Analyze Infeasible and Unbounded Models

LINDO API 1.1 includes a set of tools that allow you to track down what has caused a model to be infeasible or unbounded. The tools isolate a portion of the original model as the source of the problem. This allows you to focus your attention on a relatively small subsection of the model to look for formulation or data entry errors. On infeasible models, the tools can find an irreducibly inconsistent set of constraints (IIS), and on unbounded models, the tools can find an irreducibly unbounded set of columns (IUS).

For general information on the latest version of the LINDO API, visit our product page. To try a limited capacity version of LINDO API, see our download page, to order a copy of LINDO API or update an older version, go to our order page.

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