5 Key Areas Where Mathematical Optimization Can Deliver Benefits for Telecom Companies

Don’t Go It Alone. Gurobi and Its Partners Provide the Continuum of Support You Need.

Strengthening Mathematical Formulations in Optimization Applications

Tech Talk & Chat– Converting Weak to Strong MIP Formulations, Part II

Tata Steel: Streamlining Steel Production

Operations Research Analyst: The Fastest-Growing Job You've Never Heard Of

Delhivery: Making the Last Mile More Efficient

Choosing a Math Programming Solver

Finding Mathematical Optimization in Unexpected Places: Games and Puzzles

Campify: Optimizing Camp Schedules

Arute Solutions: Cash+ Keeps ATMs Optimally Stocked

Mathematical Optimization: What’s In A Name?

Combining Machine Learning and Optimization Modeling in Fantasy Basketball

How Better Optimization Can Solve Supply Chain Issues

Mondelēz: A Smarter Way to Ship Snacks

Tech Talk & Chat– Converting Weak to Strong MIP Formulations

Proven Techniques for Solving Financial Problems with Gurobi

Swissport: Automating Airport Staff Scheduling

Optimizing the Operation and Planning of Modern Power Systems

Why Gurobi?

Alpiq: Keeping Hydroelectric Power Flowing

Holiday Tech Talk - Santa’s Bag of Interesting & Unusual Optimization Applications

Launch Event: What’s New in Gurobi 9.5 (Chinese Language)

Boost Profitability and Efficiency with Optimization- Insights from the 2021 Financial Services Study

What’s New in Gurobi 9.5

Using Optimization to Design a Heat Exchanger in a Chemical Plant

Tech Talk - A Practical Tour Through Non-convex Optimization

Gurobi 9.5 Delivers Enterprise Features and Even Better Performance

NordStar: Crew Planning Optimization

Faster MIPs Using Custom Heuristics

Finding Mathematical Optimization in Unexpected Places: The Art World

Tech Talk & Chat– Visualization Tools

Mathematical Optimization: A Powerful Prescriptive Analytics Technology That Belongs in Your Data Science Toolbox

Industry Solution Sheet: Oil, Gas, and Petrochemicals

Kaneka: Production Planning Optimization

The Next Step for Enterprises: Optimization Transformation

COVID-19 Hospital Capacity Management using Mathematical Models

4 Key Differences Between Mathematical Optimization and Machine Learning

Polymathian: Supply Chain Optimization in the Mining Industry

Interview: How Mathematical Optimization Can Help Power Today’s Energy Industry Transformation

Latest Developments in MIP Algorithms and Applications in the Power and Energy Industries (Chinese Language)

Robeco: Investment Portfolio Optimization

Industry Solution Sheet: Agribusiness

Opportunities for Optimization in the Telecom Industry: Network Planning and Data Monetization

Industry Solution Sheet: Consumer Packaged Goods (CPG)

Mathematical Optimization: An Established and Ever-Evolving Tool For Tackling Supply Chain Disruption

Emesa: Marketing Campaign Optimization

Solution Brief: Marketing Campaign Optimization

Guide: How to Optimize the Design of Your Supply Chain Network

How Optimization Can Help Your Business Prepare For A Possible Quantum Computing Future

3 Reasons Why Mathematical Optimization Is Such A Potent Weapon In Combating Supply Chain Disruption

3 Main Pathways To Successful Mathematical Optimization Implementations

Portfolio Selection Optimization

Mathematical Optimization: The Key to Unlocking Opportunity in this Time of Transformation in the Electricity Industry

Interview: Using Mathematical Optimization to Address the Healthcare Challenges of COVID-19

Financial Services Solution Brief: Collateral Allocation Optimization

5 Key Areas Where Mathematical Optimization Can Deliver Benefits for Telecom Companies in 2021

How Mathematical Optimization Could Help Address The Covid-19 Vaccine Allocation Problem

Models with Products of Binary Variables

State of Mathematical Optimization Report

The Pivotal Role Of Mathematical Optimization In The 2020 Nobel Prize In Economics

Gurobi Product Brochure

Gurobi Corporate Brochure

RWTH Aachen University: Energy Hub Design Optimization

Your Journey to Success with Mathematical Optimization (Part II)

COVID-19: Healthcare Facility Capacity Optimization

Solving Bilinear Programming Problems

What Would Our World Be Like Without Mathematical Optimization?

Infographic: Optimizing Logistics Operations Across Your End-To-End Supply Chain

Yield Management

3 Reasons Mathematical Optimization Is Such a Powerful and Versatile AI Problem-Solving Technology

Efficiency Analysis

Toyota: Production Planning Optimization

What's New in the Gurobi Optimizer 9.1

How to Demonstrate the Business Value of Your Mathematical Optimization Application

Milk Collection Problem

Better Hardware for Solving Mathematical Optimization Problems? The Future is Looking Bright

Release Sheet: Version 9.1

Lost Luggage Distribution

Gurobi Support: Ensuring That You Are Successful With Optimization

Economic Planning

Protein Comparison

Vehicle Rental Optimization I and II

How Vodafone Uses Optimization to Tackle the Telecom Industry's Toughest Problems

Release Sheet: Version 9.0

3 Reasons Why Mathematical Optimization Solver Speed Matters

Constraint Optimization

Infographic: Measuring the Gurobi Impact

Industry Solution Sheet: Manufacturing (Make to Order Approach)

How A Mathematical Optimization Model Can Help Your Business Deal With Disruption

Protein Folding

Your Journey to Success with Mathematical Optimization (Part I)

Develop More Accurate Machine Learning Models with MIP

Polymathian: Multi-Utility Asset and Network Optimization

Math Jax Testing

Polymathian: Multi-Utility Asset and Network Optimization

3 Times in My Career When Mathematical Optimization Would Have Saved My Skin

Agricultural Pricing

Opencast Mining

Market Sharing

Logical Design

Industry Solution Sheet: Manufacturing (Make to Stock Approach)

Discover How You Can Boost Your Mathematical Optimization Modeling Skills With Python

Curve Fitting

Decentralization Planning

How To Synchronize Complex Routing Operations (Synched VRPs) with Gurobi

How to Exploit Parallelism in Linear and Mixed-Integer Programming

Should Your Company Be Using Mathematical Optimization? Ask Yourself These Four Questions to Find Out

Supply Network Design I and II

Logic Programming - 3D Tic-Tac-Toe

Marketing Campaign Optimization

Electrical Power Generation I and II

Industry Solution Sheet: Electric Power

How Birchbox Transformed Its Operations With Mathematical Optimization

3 Reasons Why More and More Companies Are Choosing to Use Mathematical Optimization

What-If Analysis: The Key to Unlocking the Opportunity in Uncertainty

Workforce Scheduling Problem

Ask the Experts: Geek Out On MIP with Gurobi's R&D Leaders

Sample Resource

Fireside Chat with Mike North, VP of Broadcast Planning & Scheduling for the NFL

Ask the Experts: Technician Routing & Scheduling Problem

Creating the NFL Schedule with Mathematical Optimization

KPMG: Using Optimization to Cope with Uncertainty

Technician Routing and Scheduling Problem

Polymathian: Mining Supply Chain Optimization

3 Ways That Mathematical Optimization Can Be Used to Improve Machine Learning Applications

4 Key Advantages of Deploying Your Mathematical Optimization Solver on a Dedicated Server

Learn How to Design and Deploy Optimization Applications

Industry Solution Sheet: Telecommunications

How You Can Improve Your Mathematical Optimization Application During the “Work-From-Home” Period

Industry Solution Sheet: Healthcare

Experience the Power of Mathematical Optimization

Industry Solution Sheet: Financial Services

Industry Solution Sheet: Supply Chain

Infographic: Discover the Business Benefits that Mathematical Optimization Delivers

How the FCC Uses Mathematical Optimization

5 Essential Ingredients for Mathematical Optimization Success

Kvaerner

Refinery Planning Problem

Mining Optimization

Manpower Planning

Food Manufacturing Problem

Farm Planning Problem

Factory Planning Problem I and II

Mathematical Optimization: What You Need to Know

Interview: Understanding the Business Value of Mathematical Optimization

Mathematical Optimization: Past, Present, and Future (Part 3)

Gurobi Optimization Application Demos

Jupyter Notebook Modeling Examples

Introduction To Mathematical Optimization Modeling

Coronavirus: How Mathematical Optimization Can Help Organizations Overcome Today’s Unprecedented Challenges

Gurobi Python Interface: Matrix-friendly Modeling Techniques

Infographic: How Are Companies Today Using Mathematical Optimization?

Gurobi Licenses and Resources for Academics

4 Reasons Why Data Scientists Should Add Mathematical Optimization to Their Analytics Toolbox

4 Keys to Delivering Excellent Customer Support

Production Planning Problem - Modeling Examples

Traveling Salesman Problem

Facility Location Problem

Cell Tower Coverage Problem

Offshore Wind Farming

The Traveling Salesman Problem Demo

Facility Location Problem Demo

Offshore Wind Farming Demo

Cell Tower Coverage Demo

Microsoft Research

Arauco: Supply Chain Planning Optimization

Birchbox: Subscription Box Service Optimization

Workforce Scheduling Demo

Forrester Opportunity Snapshot – “Mathematical Optimization and Machine Learning: Your Perfect AI Tech Team”

Integer Linear Programming in Computational and Systems Biology

Coronavirus: How Mathematical Optimization Can Help Mitigate Supply Chain Disruption

Mathematical Optimization: Past, Present, and Future (Part 2)

Imagine a World Without Mathematical Optimization

Gurobi 9.0 Compute Server – New Features and Enhancements

4 Key Advantages of Using Mathematical Optimization Instead of Heuristics

Mathematical Optimization: Past, Present, and Future (Part 1)

Tutorial: Mixed-Integer Linear Programming

Choosing a Math Programming Solver

eBook: Choosing a Math Programming Solver

Non-Convex Quadratic Optimization

Optimization with Python - Jupyter Notebook Modeling Examples

Level 4 - Resources for Advanced Users

Level 3 - Resources for Intermediate Users

Overview of Gurobi 9.0

Level 2 - Resources for Beginners

Level 1 - Introduction for Data Scientists

Customer Assignment Problem

Standard Pooling Problem

[Podcast] Data Science Based Decisions: Mixed-Integer Programming

Best Practices for Network Design Modeling

Feature Selection for Forecasting

Resource Matching Optimization Demo

Cutting Stock Problem with Multiple Master Rolls

Air France: Tail Assignment Optimization

Optimization Application Demo: Cutting Stock Problem with Multiple Master Rolls

Useful Tips and Tricks for Getting Started with Gurobi

Mathematical Optimization and Machine Learning

Fireside Chat with Ed Rothberg and Mike Watson

Integrating Machine Learning with Mathematical Optimization: Resource Matching

East Daley: Using MIP to Model Midstream Energy Assets

Tutorial: Linear Programming

Products of Variables in Mixed Integer Programming

Eurodecision: Geneva Airport Shift and Personnel Planning Optimization

Using MIP to Model Midstream Energy Assets

Portland Public Schools Redistricting

Easy Park: Urban Parking Optimization

Gurobi Optimization Application Demos

Switching from OPL

Uber: Shaping Urban Aerial Ridesharing

Exporting MPS Files Using CBC APIs: Command Line, C / C++ and Python

Adding Optimization to Your Data Science Analytics Toolbox

Advanced Methods for Optimal Scheduling Using Gurobi

The Grain Drain: Large-Scale Grain Port Terminal Optimization

A Deep Dive into Advanced Analytics Model Review and Validation

Solving Simple Stochastic Optimization Problems with Gurobi

Six Life Lessons You Didn’t Learn From Your OR Program

External Resources

Cloud Guide

AMPL Gurobi-Guide

Reference Manual

Example Tour

Quick Start Guides

Documentation

SwissQuant: Portfolio Optimization

RWTH Aachen University: Teaching

RITE Institute: Power Production

Hewlett-Packard: Project Portfolio Optimization

Tokyo University, Department of Logistics and Information Engineering

ICRON: Supply Chain Optimization

Complevo: Optimal Workforce Planning

Advanced Microgrid Solutions

Blue Yonder: Retail Pricing Decisions

Third-Party Tools for Gurobi

Recent Bug Fixes by Version

Yutong Bus: Production Planning

Wincor Nixdorf: Cash Management

Vidale Consulting Services: Mining

Parallel and Distributed Optimization with Gurobi

Integrating Gurobi into State-of-the-Art Application Architectures

Tokyo Metropolitan University: Power Minimization for Water Supply

Using Gurobi to Optimize Distributed Energy Storage Assets

Opalytics Custom Development and Cloud Deployment

Developing and Deploying Optimization Applications with AMPL

The Energy Authority: Water Routing

Intro to Performance Tuning for Optimization Systems with Gurobi

Migrating from Excel-based planning tools to enterprise-ready optimization models and applications

Pentair Water Solutions: Production

Combining Optimization with Machine Learning Webinar, Part 1

National Football League Scheduling

Avoiding Numerical Issues in Optimization Models

Better Solutions Through Effective Parameter Setting

Using the Automatic Parameter Tuning Tool

Improving the Performance of the Gurobi Optimizer

Combining Optimization with Machine Learning Webinar, Part 2

Gurobi QCP and SOCP Optimizer Overview

National Institute for Environmental Studies

Switching to Gurobi From Another Solver

Tips and Tricks for Optimal Scheduling Using Gurobi

Interactive Shell Overview Video

Modeling With the Gurobi Python Interface

Using Gurobi and Anaconda Together

Lufthansa Flight Training GmbH

Python III: Optimization and Heuristics

Python II: Advanced Algebraic Modeling with Python and Gurobi

Python I: Introduction to Modeling with Python

LeanLogistics Supply Chain Optimization

Improvements in Gurobi v7.0

Improvements in Gurobi v7.5

Improvements in Gurobi v8.0

Gurobi 8.0 - Enhancements to Instant Cloud and Compute Server

Gurobi 8.0 - Latest Enhancements to R and MATLAB APIs

Enabling Client-Server Optimization Applications With the New Gurobi Compute Server

Getting Started with Gurobi, Part 3 of 3

Getting Started with Gurobi, Part 2 of 3

Getting Started with Gurobi, Part 1 of 3

Tour of the Gurobi Optimizer

How Supply Chain Companies Can Achieve Decision-Centric Optimization

Labor Strategy Optimization for the Professional Services Industry

Ogimoto Laboratory, Balancing Power Supply and Demand

Copenhagen Airports Check-in Counter

How Optimization Modeling Creates Value for an Organization

What’s New – Current Release

Free Online Version of AMPL

Copenhagen Airport Gate and Stand Assignment

Brain Pad Online Advertising Optimization

German First Division Basketball League Scheduling

Learning More: External Books and Blogs

Building a Business Case for Optimization

Use Benchmarks to Find the Best Solver for Your Needs

The Gurobi Python Modeling and Development Environment

Mixed-Integer Programming (MIP) - A Primer on the Basics

Linear Programming (LP) - A Primer on the Basics

Math Programming Modeling Basics

Starting with Gurobi

Modeling Examples

Functional Code Examples

Switching Within a Modeling Language

Open Source Linear and Mixed-Integer Programming Software and Solvers

Switching from XPRESS

CPLEX - Switch to Gurobi

Exporting MPS Files

Why Choose Gurobi?

Switching Is Easier than You Think