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

Welcome to AMPL (A Mathematical Programming Language), a powerful and intuitive modeling language designed specifically for large-scale optimization problems. If you are new to modeling languages or AMPL, this page will guide you through what AMPL is, its benefits, and why it stands out in the landscape of programming and modeling languages.

An introduction to algorithms and computational complexity to solve combinatorial optimization problems

CVXPY is an open source Python-embedded modeling language for convex optimization problems. It lets you express your problem in a natural way that follows the math, rather than in the restrictive standard form required by solvers.

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

GAMS is a modeling system for mathematical optimization that lets users formulate complex problems in a high-level language and run them with different commercial and open-source solvers. All solvers are packaged in a single distribution, making it easy to switch between them and giving customers one point of contact for licensing and support. It also has a Python interface -GAMSPy- for building and solving mathematical optimization models using the GAMS technology stack. It keeps the modeling concepts of GAMS (sets, parameters, variables, equations) but exposes them as Python classes and functions. This allows modelers to stay in the Python ecosystem while using mature GAMS solvers and workflows.

Open source software suite for optimization, tuned for tackling the world's toughest problems in vehicle routing, flows, integer and linear programming, and constraint programming.

A gentle introduction to optimization with Python.

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

One puzzle every week.

Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness.

An introduction to Operations Research with theory from Linear Programming to simulation, passing through Nonlinear Programming, Game Theory, Metaheuristics or Network flows, among others.

JuMP is a domain-specific modeling language for mathematical optimization embedded in Julia. JuMP makes it easy to formulate and solve a range of problem classes, including linear programs, integer programs, conic programs, semidefinite programs, and constrained nonlinear programs.

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

MiniZinc is a high-level constraint modelling language that allows you to easily express and solve discrete optimisation problems.

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.

A discussion about books focused on duality theory

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

A book covering the basics of Operations Research

Business Intelligence using optimal decision making tools.

This book offers an up-to-date description of relaxation/approximation and decomposition techniques, demonstrating how their combined use efficiently solves large-scale optimization problems relevant to engineering, particularly in electrical, and industrial engineering, with a focus on energy.

An interesting book about Column Generation to tackle large-scale optimization problems

Optlang is a Python package implementing a modeling language for solving mathematical optimization problems, i.e. maximizing or minimizing an objective function over a set of variables subject to a number of constraints. Optlang provides a common interface to a series of optimization tools, so different solver backends can be changed in a transparent way.

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

An LP modeler written in Python

Laura Albert’s newsletter about OR.

Python-based, open-source optimization modeling language with a diverse set of optimization capabilities.

PyOptInterface is an open-source Python library to provide a unified API to construct and solve optimization models with various optimizers.

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