Find your next solver

Advanced Analytics in Practice focusing on breaking down what it takes to build real-world advanced analytics applications.

AGI? No, thank you! Learning and Intelligent Optimization? Yes, please! https://intelligent-optimization.org/

Learn more about how AI is changing businesses and how you can leverage it: Insights, tools, tips, and expert voices

BARON is the industry-leading solver for mixed-integer nonlinear programming (MINLP).

The CVRPLIB team announces the CVRPLIB BKS Challenge, a 30-day competition aimed at finding extremely high-quality solutions for the new XL benchmark set, 100 challenging CVRP instances ranging from 1,000 to 10,000 customers.

Ceres Solver is an open source C++ library for modeling and solving large, complicated optimization problems. It can be used to solve Non-linear Least Squares problems with bounds constraints and general unconstrained optimization problems.

The CG:SHOP Challenge (Computational Geometry: Solving Hard Optimization Problems) is an annual competition dedicated to tackling specific, difficult geometric optimization problems. Originally established as a workshop at Computational Geometry Week (CG Week) in 2019, the Challenge provides a unique platform where the success of proposed solutions is measured based on computational performance on a set of carefully selected benchmark instances. This focus on empirical evaluation marks a shift from traditional computational geometry research, which often emphasizes theoretical approaches.

An Open-Source java library for constraint programming

Chuffed is a state of the art lazy clause solver designed from the ground up with lazy clause generation in mind.

http://clarabel.rs/ is a Rust implementation of an interior point numerical solver for convex optimization problems using a novel homogeneous embedding.

Consortium for Mathematics and its applications

COMAP's Mathematical Contest in Modeling (MCM) and Interdisciplinary Contest in Modeling (ICM) are international contests for high school students and college undergraduates. The contests challenge teams of up to three students to analyze, model, solve, and present solution reports to an open-ended application problem. In these contests research, analytics, and applied intelligence are just as important as time management and problem selection. Are you and your team up to it?

CONOPT is a feasible path solver based on advanced active set methods, particularly suited for large and sparse models.

A mathematical optimization solver for large-scale optimization problems. It is independently developed by Cardinal Operations, and it includes high-performance solvers for LP, MIP, SDP, (MI)SOCP, convex (MI)QP, convex (MI)QCP and exponential cone programming.

The IBM ILOG CPLEX Optimizer solves integer programming problems, very large[3] linear programming problems using either primal or dual variants of the simplex method or the barrier interior point method, convex and non-convex quadratic programming problems, and convex quadratically constrained problems (solved via second-order cone programming, or SOCP).

Achieve world-record speed on large-scale problems with millions of constraints and variables—saving time and reducing costs.

Community for Decision Management, including Machine Learning and Optimization

Challenges from the Center for Discrete Mathematics and Theoretical Computer Science

Where Operations Research practitioners share real-world strategies and emerging techniques for optimal decision-making.

The FICO Xpress optimizer is a commercial optimization solver for linear programming (LP), mixed integer linear programming (MILP), convex quadratic programming (QP), convex quadratically constrained quadratic programming (QCQP), second-order cone programming (SOCP) and their mixed integer counterparts. Xpress includes a general purpose non-linear solver, Xpress NonLinear, including a successive linear programming algorithm (SLP, first-order method), and Artelys Knitro (second-order methods).

GCG is a generic decomposition solver for mixed-integer programs (MIPs). It automatically performs a Dantzig-Wolfe reformulation and runs a full-fledged branch-price-and-cut algorithm to solve it to optimality. Alternatively, GCG is able to automatically apply a Benders decomposition.

Gecode is an open source C++ toolkit for developing constraint-based systems and applications. Gecode provides a constraint solver with state-of-the-art performance while being modular and extensible.

For solving large-scale linear programming (LP), mixed integer programming (MIP), and other related problems. It is a set of routines written in ANSI C and organized in the form of a callable library.

Grid Optimization challenges for electric systems

Gurobi Optimizer is a prescriptive analytics platform and a decision-making technology developed by Gurobi Optimization, LLC. The Gurobi Optimizer (often referred to as simply, “Gurobi”) is a solver, since it uses mathematical optimization to calculate the answer to a problem.

Heuristic-based solver with great results in complex problems

HiGHS is open-source software to solve linear programming (LP), mixed-integer programming (MIP), and convex quadratic programming (QP) models.

To solve a sparse symmetric system of linear equations.

Huub is a Lazy Clause Generation (LCG) solver with a focus on modularity and maintainability in addition to speed. LCG solvers are a class of solvers that can be used to solve decision and optimization problems. They are characterized by their ability to dynamically add new Boolean variables and clauses to a Boolean Satisfiability (SAT) solver during the search process

Analytics, Data Science, and AI - Actionable insights and thoughts to drive positive business transformation and impact.

Optimization software that leverages machine learning to provide unparalleled performance.

One puzzle every week.

Ipopt (Interior Point Optimizer, pronounced "Eye-Pea-Opt") is an open source software package for large-scale nonlinear optimization. It can be used to solve general nonlinear programming problems

jMetal is a Java-based framework for multi-objective optimization with metaheuristics.

Challenges around TSP variant with Santa Claus

An innovative constraints programming component able to solve quickly and efficiently a wide range of combinatorial problems relying on an interactive and user-friendly hybrid framework including constraint programming, mixed-integer programming and artificial intelligence.

The most advanced solver for nonlinear optimization.

The 2026 Land-Doig MIP Competition is a computational competition hosted by the 2026 Mixed Integer Programming Workshop, offering an opportunity for teams to showcase their practical and computational prowess and fostering innovation in computational MIP. It is named in honor of Ailsa H. Land and Alison G. Harcourt (née Doig), who proposed the first LP-based branch-and-bound algorithm.

LGO is capable of determining high-quality solutions to global optimization problems that have (possibly many) locally optimal solutions. Because LGO makes only limited assumptions as to problem structure and differentiability, it can be applied in a broad range of design and operational applications.

LINGO includes a set of built-in solvers to tackle a wide variety of problems. Unlike many modeling packages, all of the LINGO solvers are directly linked to the modeling environment.

LOQO is a powerful solver for smooth constrained optimization problems, based on interior-point method applied to a sequence of quadratic approximations. Subject to the requirement that the defining functions be smooth (at the points evaluated by the algorithm), LOQO can handle a range of problems: linear or nonlinear, convex or nonconvex, constrained or unconstrained. For convex problems, LOQO finds a globally optimal solution; otherwise, it iterates from the given starting point to find a locally optimal solution.

A Mixed Integer Linear Programming (MILP) solver.

Practical AI for business, my experience starting and selling a company, and other content.

MINOS is an established choice for both linear and nonlinear optimization problems. It incorporates proven methods for large-scale sparse nonlinear constraints, and its methods are especially effective for nonlinear objectives subject to linear and near-linear constraints.

An extensible framework for solving discrete optimization problems using a combination of Mixed-Integer Linear Programming (MIP) and Machine Learning (ML). MIPLearn uses ML methods to automatically identify patterns in previously solved instances of the problem, then uses these patterns to accelerate the performance of conventional state-of-the-art MIP solvers such as CPLEX, Gurobi or XPRESS.

Annual challenges from the University of Lehigh

Solves your LPs, QPs, SOCPs, SDPs, and MIPs. Includes interfaces to C, C++, Java, MATLAB, .NET, Python, Julia, Rust and R.

A gradient-free optimization platform.

Roundup of Operations Research, Decision Science, and DecisionOps content from Nextmv and the optimization community

NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms.

Challenges with different optimization problems

Business Intelligence using optimal decision making tools.

The OSQP (Operator Splitting Quadratic Program) solver is a numerical optimization package for solving convex quadratic programs.

Challenge from Parameterized Algorithms and Computational Experiments Challenge to bridge the gap between theory and practice of algorithms

The PATH solver for MCP models is a Newton-based solver that combines a number of the most effective variations, extensions, and enhancements of this powerful technique.

PATHNLP is a solver for large nonlinear programming problems that builds on the PATH algorithm, extending it from mixed complementarity problems to general NLPs. PATHNLP is distributed through the GAMS ecosystem.

Planning education for real-world stuff, the newsletter for problem solvers at scale.

🌟 Welcome to the Prescriptive Analytics and Decision Optimization (PRADO) Series 2025! 🌟 The series of presentations about OR in practice, tools, and technologies. 📅 Program Sneak Peek: 🎤 March: Optimizing pharmacy procurement with substitution of drugs

Laura Albert’s newsletter about OR.

Bi-annual challenges from the French Operational Research (OR) and Decision Support Society. 2026: https://gitlab.com/Orange-OpenSource/network-optimization-tools/challenge-roadef-2026/-/tree/main/sprint_results

SBB is a GAMS solver for Mixed Integer Nonlinear Programming (MINLP) models. It is based on a combination of the standard Branch and Bound (B&B) method known from Mixed Integer Linear Programming and some of the standard NLP solvers already supported by GAMS. SBB can use all GAMS NLP solvers as subsolvers but it works best with NLP solvers that can utilize a near optimal point as a starting point like Conopt, Minos, and Snopt.SBB supports all types of discrete variables supported by GAMS, including Binary, Integer, Semicont, Semiint, Sos1, and Sos2.

SCIP is currently one of the fastest non-commercial solvers for mixed integer programming (MIP) and mixed integer nonlinear programming (MINLP). It is also a framework for constraint integer programming and branch-cut-and-price.

SCS (Splitting Conic Solver) is a numerical optimization package for solving large-scale convex quadratic cone problems. The code is freely available on https://github.com/cvxgrp/scs. It solves primal-dual problems.

Annual challenges organized by Shell AI team.

SHOT (Supporting Hyperplane Optimization Toolkit) is a deterministic solver for mixed-integer nonlinear programming problems (MINLPs). Originally, SHOT was intended for convex MINLP problems only, but now also has functionality to solve nonconvex MINLP problems as a heuristic method without providing any guarantees of global optimality. SHOT can solve certain nonconvex problem types to global optimality as well.

Optimization competition organized by the Mexican Society of Operations Research (SMIO).

A software package for solving large-scale optimization problems (linear and nonlinear programs). It employs a sparse SQP algorithm with limited-memory quasi-Newton approximations to the Hessian of Lagrangian. SNOPT is especially effective for nonlinear problems whose functions and gradients are expensive to evaluate.

Advice from a decision strategist with 19 years expertise in analytics & AI, inc. Gartner, system integrators & industry

Updated fork from OptaPlanner

Uno (Unifying Nonlinear Optimization) is a C++ library that unifies methods for solving nonlinearly constrained optimization problems.

Vehicle Routing and Logistics work group from EURO

Z3 is a theorem prover from Microsoft Research.