TRY NOW!
AMPL > >Products > >Solvers > >Solvers We Sell

Solvers We Sell

We offer a selection of the highest-quality solvers, interfaced to AMPL for full access to algorithms and options. For your convenience we provide licensing and support on the same terms as the AMPL software. Our price list includes all of these solvers in a range of configurations.

The choice of a solver is determined mainly by the kind of problem to be solved and the optimizing algorithms to be applied. Usually several solvers are applicable to the problems that derive from a particular application; as solver performance is highly application-dependent, a choice among solvers is best made by testing on representative examples. Our free trials of AMPL include any selection of these solvers.

Our solver lineup is summarized below, with links to more detailed descriptions. We group the solvers into “linear” and “nonlinear” types according to the type of problem for which they are primarily used, though there is some overlap in function.

Linear solvers

These solvers all handle linear and convex quadratic optimization problems in both continuous and integer variables. They incorporate fast primal simplex, dual simplex, and interior methods for linear programming together with sophisticated branch-and-cut and heuristic search approaches for pure-integer and mixed-integer problems. Options for parallel computation are included:

These are the most widely used kind of solver for applications throughout business planning and operations and for many financial models.

Nonlinear solvers

The solvers in this category provide the most effective way of finding locally optimal solutions to problems involving smooth nonlinear functions such as powers, logs, and ratios. They differ in the algorithms that they offer, and hence in their effectiveness for different problem types:

  • CONOPT (ARKI Consulting & Development) — multi-method architecture founded on reduced gradient
  • KNITRO (Ziena Optimization) — choice of interior-point and active-set methods, with support for integer variables and automatic multiple starts
  • MINOS (Stanford University) — sophisticated reduced gradient approach founded on a linear primal simple method
  • SNOPT (Stanford University) — sequential quadratic approximation method

Nonlinear solvers are used extensively in applications such as energy transmission and engineering design that have a physical component, and in advanced economic and financial applications.