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Benchmarks
Blog
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Adopting Optimization in Your Organization

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Ask the Experts: Technician Routing & Scheduling Problem
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Building a Business Case for Optimization
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Choosing a Math Programming Solver
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Creating the NFL Schedule with Mathematical Optimization
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Develop More Accurate Machine Learning Models with MIP
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Fireside Chat with Mike North, VP of Broadcast Planning & Scheduling for the NFL
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Gurobi Optimization Application Demos
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How Birchbox Transformed Its Operations With Mathematical Optimization
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How Optimization Modeling Creates Value for an Organization
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How Supply Chain Companies Can Achieve Decision-Centric Optimization
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How Vodafone Uses Optimization to Tackle the Telecom Industry’s Toughest Problems
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How the FCC Uses Mathematical Optimization
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How to Exploit Parallelism in Linear and Mixed-Integer Programming
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Integrating Gurobi into State-of-the-Art Application Architectures
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KPMG: Using Optimization to Cope with Uncertainty
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Labor Strategy Optimization for the Professional Services Industry
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Mathematical Optimization and Machine Learning
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Models with Products of Binary Variables
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Six Life Lessons You Didn’t Learn From Your OR Program
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Solving Bilinear Programming Problems
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What’s New in the Gurobi Optimizer 9.1
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[Podcast] Data Science Based Decisions: Mixed-Integer Programming

Gurobi Partner Videos

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A Deep Dive into Advanced Analytics Model Review and Validation
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Advanced Methods for Optimal Scheduling Using Gurobi
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Combining Optimization with Machine Learning Webinar, Part 1
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Combining Optimization with Machine Learning Webinar, Part 2
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Developing and Deploying Optimization Applications with AMPL
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Fireside Chat with Ed Rothberg and Mike Watson
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How To Synchronize Complex Routing Operations (Synched VRPs) with Gurobi
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Integer Linear Programming in Computational and Systems Biology
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Migrating from Excel-based planning tools to enterprise-ready optimization models and applications
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Opalytics Custom Development and Cloud Deployment
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The Grain Drain: Large-Scale Grain Port Terminal Optimization
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Tips and Tricks for Optimal Scheduling Using Gurobi
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Using MIP to Model Midstream Energy Assets

Videos Introducing Gurobi

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Adding Optimization to Your Data Science Analytics Toolbox
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Ask the Experts: Geek Out On MIP with Gurobi’s R&D Leaders
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Enabling Client-Server Optimization Applications With the New Gurobi Compute Server
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Getting Started with Gurobi, Part 1 of 3
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Getting Started with Gurobi, Part 2 of 3
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Getting Started with Gurobi, Part 3 of 3
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Gurobi 8.0 – Enhancements to Instant Cloud and Compute Server
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Gurobi 8.0 – Latest Enhancements to R and MATLAB APIs
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Improvements in Gurobi v7.0
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Improvements in Gurobi v7.5
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Improvements in Gurobi v8.0
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Integrating Machine Learning with Mathematical Optimization: Resource Matching
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Overview of Gurobi 9.0
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Tour of the Gurobi Optimizer
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Useful Tips and Tricks for Getting Started with Gurobi

Videos on Modeling with Gurobi

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Best Practices for Network Design Modeling
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Gurobi QCP and SOCP Optimizer Overview
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Interactive Shell Overview Video
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Learn How to Design and Deploy Optimization Applications
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Non-Convex Quadratic Optimization
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Products of Variables in Mixed Integer Programming
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Switching to Gurobi From Another Solver

Videos on Modeling with Gurobi and Python

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Gurobi Python Interface: Matrix-friendly Modeling Techniques
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Modeling With the Gurobi Python Interface
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Python I: Introduction to Modeling with Python
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Python II: Advanced Algebraic Modeling with Python and Gurobi
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Python III: Optimization and Heuristics
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Using Gurobi and Anaconda Together

Videos on Parallel and Distributed Optimization

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Parallel and Distributed Optimization with Gurobi
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Using Gurobi to Optimize Distributed Energy Storage Assets

Videos on Tuning Gurobi's Performance

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Avoiding Numerical Issues in Optimization Models
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Better Solutions Through Effective Parameter Setting
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Improving the Performance of the Gurobi Optimizer
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Intro to Performance Tuning for Optimization Systems with Gurobi
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Solving Simple Stochastic Optimization Problems with Gurobi
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Gurobi 9.0 Compute Server – New Features and Enhancements