Capabilities: 
  • Best-in-Class Optimization Engines
  • Solves up to millions of decision variables and constraints
  • Available in Excel and the Cloud
  • Can be controlled code in C++, C#, Java, PHP, JavaScript and other languages.
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Best-in-Class Optimization Engines for the World's Most Challenging Problems

Go from thousands to hundreds of thousands or even millions of decision variables and constraints.

The built-in engines included with our Solver Platform products can handle problems with thousands of variables and constraints, and offer great performance at no extra cost. But what if your model is larger, or it takes longer to solve than you'd like? Frontline has brought the world's best Solvers to our platform -- enabling users like you to solve nonlinear models with 100,000 variables or more, and linear models with millions of variables.

For large-scale problems, it's especially important to understand the type of model -- linear, non-linear or non-smooth, convex or non-convex -- you are trying to solve, improve the formulation if possible, and choose the best Solver Engine. To learn more, visit Optimization Problem Types. Fortunately, you can try any of our 8 plug-in large-scale Solver Engines free for 15 days -- and our Excel Solver Platform products can algebraically diagnose your model and automatically select the best Solver Engine, choosing from the all the available built-in and plug-in Solver Engines.

These Solver engines "plug into" either Platform product. You select them from the Solver engine dropdown list, just as you do for the built-in Solvers, and you can display and change their options and parameters in the same way as built-in Solver engines. They can be interrupted during the solution process by pressing the ESC key, and they produce reports in spreadsheet form, just like the built-in Solver engines. They can be controlled by your VBA code using the APIs supported by all our Excel Solver Platform products. And the same Solver Engines can be used with our Solver SDK Platform product, and controlled by your code in C++, C#, Java, PHP, JavaScript and other languages.

Linear and Quadratic Programming Problems

Solver Engine

Variables

Constraints

Features

Std. Large-Scale LP/QP Solver

32,000

32,000

Sparsity, factorization

Ext. Large-Scale LP/QP Solver

Unlimited

Unlimited

Sparsity, factorization

MOSEK Solver

Unlimited

Unlimited

Also handles QCP, SOCP, convex NLP models

Large-Scale SQP Solver

Unlimited

Unlimited

Also handles NLP, NSP models

XPRESS Solver Engine

Unlimited

Unlimited

Sparsity, dual Simplex, Barrier method, MIP performance

Gurobi Solver Engine

Unlimited

Unlimited

Sparsity, dual Simplex, best MIP performance

You can also use large-scale nonlinear Solver engines with our Solver Platforms to solve large-scale LP problems, but the above Solver engines offer much better performance on such problems.  All of the above Solver Engines are typically very fast on large-scale LP problems.  Note: Solution of large-scale QP problems using any of these Solver Engines may be limited by available memory.

Conic Optimization Problems

Solver Engine

Variables

Constraints

Features

Ext. Large-Scale GRG Solver

12,000

12,000

Sparsity, degeneracy handling

MOSEK Solver

Unlimited

Unlimited

Also handles smooth convex NLP models

Large-Scale SQP Solver

Unlimited

Unlimited

Also handles smooth NLP models

Artelys Knitro Solver

Unlimited

Unlimited

Also handles smooth NLP models

Gurobi Solver Engine

Unlimited

Unlimited

Also handles QP and QCP models (not NLP models)

The MOSEK Solver is designed for conic optimization, and offers the best performance on SOCP problems.  The Large-Scale GRG Solver, Large-Scale SQP Solver and Knitro Solver are designed to solve both convex and non-convex NLP problems, but they also handle second order cone (SOC) constraints.

Integer and Constraint Programming Problems

Solver Engine

Variables

Constraints

Features

Std. Large-Scale LP/QP Solver

32,000

32,000

Cut generation, heuristics, dual Simplex, many others; up to 32,000 integer variables

Ext. Large-Scale LP/QP Solver

Unlimited

Unlimited

Cut generation, heuristics, dual Simplex, many others; unlimited integer variables

MOSEK Solver

Unlimited

Unlimited

Cut generation, heuristics, dual Simplex, unlimited integer variables, QCP, SOCP, convex NLP models

Large-Scale SQP Solver

Unlimited

Unlimited

Basic cut generation, 0-1 probing, heuristics

XPRESS Solver Engine

Unlimited

Unlimited

Advanced cut generation, 0-1 probing, heuristics, dual Simplex, many others

Gurobi Solver Engine

Unlimited

Unlimited

Advanced cut generation and heuristics; highest performance on LP/MIP problems

Every Solver engine for our Solver Platforms will handle problems with integer variables, including variables subject to the "alldifferent" constraint.  If you have a large or challenging mixed-integer or constraint programming problem, however, the XPRESS Solver Engine or Gurobi Solver Engine may be fastest on these problems.

These Solver engines "plug into" either Platform product. You select them from the Solver engine dropdown list, just as you do for the built-in Solvers, and you can display and change their options and parameters in the same way as built-in Solver engines. They can be interrupted during the solution process by pressing the ESC key, and they produce reports in spreadsheet form, just like the built-in Solver engines. They can be controlled by your VBA code using the APIs supported by all our Excel Solver Platform products. And the same Solver Engines can be used with our Solver SDK Platform product, and controlled by your code in C++, C#, Java, PHP, JavaScript and other languages.

Smooth Nonlinear Optimization Problems

Solver Engine

Variables

Constraints

Features

Ext. Large-Scale GRG Solver

12,000

12,000

Sparsity, degeneracy handling

MOSEK Solver

Unlimited

Unlimited

Sparsity, capacity, speed on convex NLP models

Large-Scale SQP Solver

Unlimited

Unlimited

Sparsity, capacity, speed

Artelys Knitro Solver

Unlimited

Unlimited

Sparsity, capacity, speed

The MOSEK Solver can handle very large smooth convex NLP problems, but it does not support non-convex problems.  The Large-Scale SQP Solver can solve very large smooth convex and non-convex NLP problems, but its practical upper limit on the degrees of freedom (i.e. the number of variables minus the number of constraints that are binding at the solution) is about 2,000. Thanks to both interior point methods and active-set methods, the Knitro Solver can handle the largest smooth convex and non-convex NLP models, and the number of degrees of freedom can be much larger than 2,000.

You can also use Solver engines designed for global and nonsmooth optimization with our Solver Platforms to solve smooth NLP problems, but the above Solver engines offers better performance on such problems.

Global Optimization Problems

Solver Engine

Variables

Constraints

Features

OptQuest Solver

5,000

1,000

Tabu search, scatter search

Ext. Large-Scale GRG Solver

See below

See below

Multistart methods

Large-Scale SQP Solver

See below

See below

Multistart methods

Artelys Knitro Solver

See below

See below

Multistart methods

The OptQuest Solver finds global solutions and also handles nonsmooth problems, but it has no test for global optimality.  The other Solver Engines use the Premium Solver Platform's multistart or clustering methods to seek all locally optimal solutions, and select the best of these as the probable globally optimal solution. 

Although these Solver Engines accept large or unlimited size problems, the practical limit for global optimization problems is much lower -- comparable to the OptQuest Solver.

Nonsmooth Optimization Problems

Solver Engine

Variables

Constraints

Features

OptQuest Solver

5,000

1,000

Tabu search, scatter search

Large-Scale SQP Solver

Unlimited

Unlimited

Evolutionary Solver plus SQP

The OptQuest Solver is designed for nonsmooth optimization, and offers very good performance on arbitrary Excel models, especially if they include integer variables.  The Large-Scale SQP Solver integrates the Evolutionary Solver (which uses both genetic algorithms, and tabu search/scatter search methods employed by the OptQuest Solver) and is very effective for problems with some nonsmooth, and other smooth and linear, variable occurrences -- but the practical limit on nonsmooth variables and constraints is much lower than for smooth problems.

You can try Solver engines designed for smooth non-convex nonlinear optimization on nonsmooth problems, but they may not successfully deal with nonsmooth or discontinuous functions that are important to the model.

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Whichever product you buy, we offer a full range of support internally and through external partners to help you succeed. Whether you are looking for pre-sales support on your problem and our product line, Technical Support on using our tools, or personalized Consulting Services, we are here to help you. We offer a full range of online support resources you can access anytime.

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