# Comparison of optimization software
## Links (Wikipedia order)
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`AIMMS` · `ALGLIB` · `AMPL` · `ANTIGONE` · `APMonitor` · `APOPT` · `Artelys_Knitro` · `BARON` · `COIN-OR` · `CPLEX` · `CasADi` · `Constraint_(mathematics)` · `Constraint_programming` · `Couenne` · `ECLiPSe` · `Euclidean_space` · `FICO_Xpress` · `FortMP` · `Function_(mathematics)` · `GLOP` · `GNU_Linear_Programming_Kit` · `GNU_Scientific_Library` · `Galahad_library` · `Gecode` · `Gekko_(optimization_software)` · `Global_optimization` · `Gurobi_Optimizer` · `HiGHS_optimization_solver` · `IMSL_Numerical_Libraries` · `IPOPT` · `JaCoP_(solver)` · `JuMP` · `LINDO` · `LIONsolver` · `Linear_programming` · `List_of_optimization_software` · `Lp_solve` · `MIDACO` · `MINOS_(optimization_software)` · `MINTO` · `MOSEK` · `MPS_(format)` · `Math_Kernel_Library` · [[Mathematical_optimization]] · `Mathematical_programming_with_equilibrium_constraints` · `MiniZinc` · `NLPQLP` · `NMath` · `NPSOL` · `Nl_(format)` · `Nonlinear_programming` · `OR-Tools` · `Octeract_Engine` · `OptimJ` · `Optimization_problem` · `Pyomo` · `Quadratic_programming` · `Quadratically_constrained_quadratic_program` · `Real_number` · `Robert_J._Vanderbei` · `SNOPT` · `SciPy` · `Second-order_cone_programming` · `Semidefinite_programming` · `Set_(mathematics)` · `Sol_(format)` · `Solver` · `Subset` · `TOMLAB` · `WORHP` · `Wolfram_Mathematica`
> Summary stub · part of Systems Engineering · [Wikipedia source](https://en.wikipedia.org/wiki/Comparison_of_optimization_software)
## Summary
This article compares software for [[Mathematical_optimization|mathematical optimization]], the tools used to find the best solution to problems subject to constraints, spanning linear, nonlinear, integer, and convex programming. Optimization solvers are central to [[Operations_research|operations research]], [[Engineering|engineering]] design, [[Logistics|logistics]], and [[Machine_learning|machine learning]]. Well-known examples include the commercial solvers CPLEX and Gurobi and the open-source COIN-OR project. The article surveys their capabilities and supported problem types.
## Key points
- Compares mathematical optimization software
- Covers linear, nonlinear, integer, and convex programming
- Central to operations research and design
- Examples include CPLEX, Gurobi, and COIN-OR
- Surveys solver capabilities and problem types
## Relation to Systems Engineering
Optimization is how systems engineers select the best design among alternatives subject to constraints, making these solvers core trade-study tools.
## Sources
- [Comparison of optimization software — Wikipedia](https://en.wikipedia.org/wiki/Comparison_of_optimization_software)
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## Wikipedia : Wikitube
**Strict pair:** [Wikipedia](https://en.wikipedia.org/wiki/Comparison_of_optimization_software) : [Wikitube](https://en.wikitube.io/wiki/Comparison_of_optimization_software)
## Previous hub tags
Tree parent: [[Systems_engineering]].
Legacy hubs: none.
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*Sources: 1 legacy note. Minted wave 1, 2026-07-30 (v1.6 order).*