Find your next solver

Decision Science Leader at Toyota sharing career development tips.

Operations Research Engineer at Réseau de Transport d'Électricité that shares optimization knowledge in his YouTube channel, Aligorithm.

Lead Data Scientist at Bluecrux with a newsletter about Constraint Programming.

Sales at Gurobi, shares interesting posts about Gurobi.

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.

Associate Professor at Universidade Federal da Paraíba + Host of the “Subject to” podcast.

Optimization Expert | Algorithm Design | Operations Research

Lead Operations Research Engineer at Trucksters with a newsletter about all things Operations Research.

PhD Operations Research | Lead Engineer @ FICO

Operations Research Scientist at Amazon, shares pragmatic views about delivering value through OR.

Co-Founder + CEO at Nextmv.

Operations Research Expert | Senior Consultant @ Capgemini Invent

Lecturer || Funded Investigator || Logistics, Supply Chain and Smart Manufacturing

Optimization Data Scientist at MaxAB, spreads the OR word through stories.

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.

Professor in Operations Research at Copenhagen Business School; Editor-in-Chief of TOP, the OR journal of SEIO.

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.

Co-Founder + CTO at Timefold AI.

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.

VP Product Strategy & Industry Solutions

Leveraging data in Logistics and Supply Chain Management | #datainlogistics | PhD in Machine Learning | Industrial Engineer

Optimization consultant at Decide4AI sharing impactful tips on coding for OR projects.

J.D. Kelly is an Advanced Planning and Scheduling (APS) and Advanced Process Control (APC) expert in the process industries including both optimization and estimation technologies otherwise known as Advanced Production-chain Control, Optimization and Estimation (APCOE)

Senior Data Scientist | Machine Learning Engineer | Decision Scientist | Optmization | Operations Research | Python | SQL | SAS

Reader in Mathematics at the University of Edinburgh

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.

Sr Operations Research Analyst at Avista

Professor of Decision and Operation Technologies at Bielefeld University.

Professor of Industrial and Systems Engineering at the University of Wisconsin-Madison, 2023 INFORMS President.

Professor of operations research at RWTH Aachen University.

Assistant Professor of Transportation Engineering @ York University | Director of Interactive-OR | Amazon Visiting Academic @ Amazon

Creator of Optimization Solvers, CEO at InsideOpt.

Principal Research Scientist | AI Planning, Reasoning, and Decision-Making Systems; Executive Council Board Member at ICAPS and at AAAI, AAAI Senior Member

Teaching and writing about all things AI, operations, and his startup experience.

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.

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.

Senior Data Scientist at Horvath who shares case studies and mini interviews.

Manager, Operations Research & Data Science | Optimization Expert (Ph.D.)

Logistics Data Scientist + Founder of Open Door Logistics.

President of Optisol, Scheduling Specialist for High-Variety, Order-Driven Production and Resource-Constrained Projects.

An LP modeler written in Python

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.

OR Scientist at American Tire Distributors. OR, Python, Interviewing Content and More.

Self-employed OR Engineer at Bluebird Optimization sharing insights about the impact of optimization in businesses.

Mathematical Optimization Researcher, Teacher, and Manager

Professor Emeritus, Princeton University/ Co-Founder, Optimal Dynamics, shares knowledge about sequential decision problems.

Senior Decision Scientist at Aimpoint Digital | Decision Sciences, Mathematical Modeling

Consultant: Solving the Meta-Problem focused on Data and Supply Chains | Data Analytics, Inventory, Lean Warehouse, Process Improvement