Find your next solver

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

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.

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

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

Discrete Optimization Talks (DOTs) is a virtual seminar series from the Mixed Integer Programming Society (MIPS), a technical section of the Mathematical Optimization Society (MOS). Topics of interest are theoretical, computational, and applied aspects of integer and combinatorial optimization. The typical format of each session is two 30-minute talks.

Heuristic-based solver with great results in complex problems

It features conversations between students, faculty and professionals around OR-related topics

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

The most advanced solver for nonlinear optimization.

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.

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.

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.

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

The Network consists of six academic and nine industrial participants from five EU countries, USA and Chile. The participants combine strong and complementary expertise, within industry sectors ranging from energy, retailing, insurance to banking, as well as national statistical offices.

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.

Discussions around optimization, interviewing academics in the field of Operations Research and Industrial Engineering

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

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.

The podcast from INFORMS that talks about different topics around Operations Research

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.

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.

"Subject to" offers a series of informal conversations with relevant figures in the fields of Operations Research, Combinatorial Optimization and Logistics, and they are hosted by Anand Subramanian, an Associate Professor at Universidade Federal da Paraíba (UFPB), Brazil

The Decision Intelligence Lab explores practical challenges of applying data science, analytics, and AI to drive real-world business outcomes. Hosted by Prof. Michael Watson (Nortwestern University) and Prof. Vijay Mehrotra (University of San Francisco) - both seasoned entrepreneurs, consultants, and researchers - this podcast delivers real-world insights for data professionals, business leaders, & anyone seeking to leverage data for smarter decision making. Each episode features leaders sharing how smarter decisions are reshaping business and technology.