The following table summarizes availability of solvers for which
interfaces to AMPL have been constructed, and provides links to
additional information in the AMPL vendor
listing and at the Web sites of individual companies. Algorithm types listed in the table are distinguished by the problems they solve and the methods they use, as follows:
If your favorite solver does not appear here, we encourage you to explore the possibility of adding it to the list. See our discussion of hooking your solver to AMPL following the solver listing.
Solver listingAll of the solvers listed below can be used with AMPL. Send additions or corrections to info@ampl.com.Algorithm Types. See above for definitions. Vendor or Download Site. Sources of further information for obtaining the solver. This entry may be a link to a developer's or vendor's web site, or (where indicated) to a site from which the solver can be downloaded. Driver Code. A link to a directory in netlib/ampl/solvers from which you can download C source code to make an AMPL driver for the solver. The driver provides an interface from AMPL's general description of an optimization problem to a solver's particular algorithms and options. Hence a different driver is needed for each solver. Some solvers are available bundled with the appropriate AMPL driver, while others require that you download and compile the driver yourself; details are available from the vendor or from the README file in the driver's netlib directory. Documentation. The README files are text copied from the netlib/ampl/solvers directory mentioned above. The Using . . . booklets can be downloaded in PDF or postscript format.

Problem analysis toolsMProbeMProbe is a tool for analyzing nonlinear functions to discern their shapes in a region of interest. MProbe is linked to AMPL, so that it may be used to analyze any nonlinear objective or constraint function written in the AMPL language.Shape means whether the function is linear or almost linear, convex or almost convex, concave or almost concave, or concave and convex. Knowledge of function shape is crucial when developing nonlinear optimization models, or when selecting the nonlinear solver for a nonlinear optimization problem. Determining function shape is difficult for nonlinear functions having more than two variables. MProbe is specifically designed to operate on nonlinear functions having many variables. MProbe 5.0 offers numerous new plotting options, sampling inside any convex enclosure (for improved accuracy of conclusions), and identification of redundant constraints and bounds. MProbe has been developed by Prof. John Chinneck of Carleton University. A student/demo version bundled with the AMPL Student Edition is available for downloading through the web.
Hooking your own solver to AMPLNew solver hookups are encouraged though AMPL's use of freely available interface routines to support flexible and fully documented file formats for problems and results.Detailed instructions and examples are available to help you (or your solver's developer) to write an AMPL driver. AMPL can then switch to your solver, set up its algorithmic options, send it a problem to be solved and retrieve the results, all in the same way that you work with currently supported solvers. See our instructions on hooking your solver to AMPL for further details.
Comments or questions? Write to info@ampl.com or use our comment form.
LAST MODIFIED 4 FEBRUARY 2014 BY 4er. 