This page contains videos that will help you get up to speed on, and get the most from, the Gurobi Optimizer. Click on the links below to learn more about each video.
|Adopting Optimization in Your Organization|
|Building the Business Case For Optimization ➤||How Optimization Can Add Value To An Organization ➤|
|Labor Strategy Optimization for a Professional Services Industry ➤||Integrating Gurobi into State-of-the-Art Application Architectures ➤|
|How Supply Chain Companies Can Achieve Decision-Centric Optimization ➤|
|Videos Introducing Gurobi|
|Tour of the Gurobi Optimizer ➤||Release overview: 8.0 ➤|
|Getting Started with Gurobi ➤||Release overview: 7.5 ➤|
|Gurobi Compute Server ➤||Release overview: 7.0 ➤|
|Gurobi 8.0 - Enhancements to MATLAB and R APIs ➤||Gurobi 8.0 - Enhancements to Compute Server and Cloud ➤|
|Videos on Modeling with Gurobi and Python|
|Python I: Introduction to modeling with Python ➤||Using Gurobi and Anaconda to build models and python applications ➤|
|Python II: Advanced Algebraic Modeling with Python ➤||Modeling with the Gurobi Python Interface ➤||Python III: Optimization and Heuristics ➤|
|Videos on Modeling with Gurobi|
|Switching to the Gurobi Solver ➤||The Gurobi Interactive Shell ➤|
|Solving Quadratically-constrained Models ➤|
|Videos on Tuning Gurobi's Performance|
|Improving the Performance of the Gurobi Optimizer ➤||Using the Automatic Parameter Tuning Tool ➤|
|Finding better solutions in less time through effective parameter setting ➤||Avoiding Numerical Issues in Optimization Models ➤|
|Introduction to Performance Tuning ➤|
|Videos on Parallel and Distributed Optimization|
|Parallel and Distributed Optimization with the Gurobi Optimizer ➤|
|Gurobi Partner Videos|
|Opalytics Cloud Platform ➤||Combining Optimization and Machine Learning Part One ➤|
|Developing and Deploying Optimization Applications with AMPL ➤||Combining Optimization and Machine Learning Part Two ➤|
|Migrating from Excel-based planning tools to enterprise-ready optimization models and applications with ORConomy and Optano ➤||Job Scheduling Tips and Tricks ➤|
In this 50 minute webinar you'll learn how successful companies are using optimization and persuasive support points to help build managerial and sernior leadership buy-in for optimization. In addition, you'll learn different ways in which optimization can drive value and actionable steps to help set up your optimzation projects for success.
In this 40-minute webinar you'll learn how to identify opportunities to leverage optimization, improve your decision-making processes and transform the role of planning in your organization.
In this 45-minute webinar you'll get introduced to a labor strategy optimization (LSO) problem to prescribe an optimal staffing plan (internal workforce, contingent/contractor workforce, training and re-skilling, and agency workforce) to meet the target revenues of a professional services firm.
In this 45-minute webinar you'll learn about the different deployment and licensing options, including support for containerized applications using Docker and Kubernetes, as well as related aspects, such as choosing the right interface, proper hardware sizing and migration to client/server architectures.
In this 40-minute webinar recording you'll learn more about decision-centric optimization, what you need in terms of data, algorithic and organizational capabilities, how Gurobi technologies facilitate optimized decision making, an overview of the ICRON platform, and an example of an electronics manufacturing customer.
This 50 minute video seminar takes you through a tour of the Gurobi Optimizer. The tour explores the interfaces that can be used to access the Gurobi Optimizer. See examples of how to work with the Gurobi matrix-based and object-oriented APIs, and learn how to use Gurobi through well-known modeling languages.
We've partnered with Abrèmod, LLC, to create a webinar geared toward newer users. The webinar topics include:
The webinar is available in three parts:
This one hour video seminar explains how you can enable client-server optimization applications with the new Gurobi Compute Server. This webinar provides an overview of the benefits of using a client-server architecture, how the Compute Server can be used, server installation and setup, using the client, and solving on the Gurobi Cloud.
This 30-minute video is an overview of significant enhancements to our R and MATLAB APIs that were added as part of Gurobi 8.0 release. Those improved APIs now provide nearly all the capabilities of other Gurobi APIs, and now support multi-objective optimization, general constraints, etc.
This 50-minute video is an overview of significant enhancements to our Compute Server and Cloud products that were improved as part of Gurobi 8.0 release, such as moving to standard communication protocols to help improve security and increase robustness, dynamic addition and removal of clusters, compute server monitoring and management capabilities, improved machine and pool management, and more.
This 30-minute video features an overview of the higher performance and expansive new features in Gurobi Optimizer, Instant Cloud and Compute Server. Those include enhanced R and MATLAB APIs, support for .NET Core 2.0, ultiple MIP starts, partition heuristic, callbacks for multi-objective optimization, standard communication protocol, clustering, commands, REST API, HTTPS support job list, job dashboard, job history, pool scaling and machine metrics. This video is also available in Deutsch, Español and 中文.
This video covers the significant performance improvements on MIP, LP, MIQP and SOCP models, Python modeling enhancements and new features users have asked for. Specifically, the topics include an overview of those Python modeling enhancements (including helper functions), the enhanced multi-objective API, new JavaDoc documentation, added support for Python 3.6, Vistual Studios 2017 and R 3.4 platforms, and new parameters, among other enhancements. This video is also available in Deutsch.
This video covers the significant performance improvements, API enhancements, and new features users have asked for. The topics include significant performance enhancements across a range of models, support for multiple objectives with flexibility in how they are prioritized, Python modeling enhancements that simplify the translation of mathematical models into efficient implementations, new general constraints where you can enter commonly occurring constraints without having to translate them into linear constraints, a new intuitive and enhanced Gurobi Instant Cloud API that simplifies instance launching and integration of the Gurobi Instant Cloud into applications, and a number of additional enhancements. This video is also available in Deutsch, Español and 中文.
This 55 minute video, part one of a three-part series, presents an introduction to using Python, Gurobi and Jupyter Notebooks. It covers the basics of model-building, including working with decision variables, constraints, objective function, sums and for-all loops.
This one-hour video, part two of a three-part series, covers more advanced topics including data structures and loops, sum and for-all expressions, working with large data sets and building large-scale, high-performance applications using the Gurobi Python interface.
This one-hour video, part three of a three-part series, covers one capability of MIP that is often overlooked: its ability to find and subsequently improve good quality solutions to exceedingly difficult problems. This webinar, which builds on the ideas presented in the last Python webinar, will focus on techniques for using the Gurobi MIP solver as a heuristic.
This 60 minute video presentation provides an overview of using Gurobi and Anaconda together to build models and python applications. It includes an overview of the Spyder IDE, Jupyter notebooks, using Pandas to manage data and Bokeh to visualize results.
The Gurobi Python interface allows you to build concise and efficient optimization models using high-level modeling constructs. This 50 minute video tutorial provides an overview of these capabilities, including detailed examples that show how to use the Python interface to build models that can be turned into full optimization applications.
This 75 minute video presentation demonstrates the capabilities of the Gurobi Interactive Shell. Working with the Gurobi Interactive Shell is the quickest way to get started with the Gurobi Optimizer. Learn all the basics of using the interactive shell: how to load and modify models, run the optimization algorithms, and much more.
In this one-hour webinar, co-presented by Gurobi and Abremod, we'll review:
These slides explain how to take software written for another optimization solver and convert it to use Gurobi Optimizer. This covers nearly every scenario: model files, modeling systems, matrix interfaces and object-oriented interfaces.
Our Gurobi 5.0 release added the ability to solve quadratically-constrained models (QCP and MIQCP). This new capability is built on top of an efficient Second-Order Cone Programming (SOCP) solver. This seminar will discuss the design choices we made in building this new optimizer, and the impact of these choices on overall performance and robustness.
This 73 minute video seminar explains how to tune the performance of the Gurobi Optimizer. There are different factors that can contribute to slow performance in solving an optimization model; learn how to recognize the different performance bottlenecks and see some techniques to cope with each situation.
This 17 minute video seminar explains the impact parameters can have on performance, tips on how to think about using parameters to improve performance, and how to use the Automatic Parameter Tuning tool included free with Gurobi to improve performance.
In this one-hour webinar, given by Gurobi CTO and Co-founder, Dr. Zonghao Gu, we'll be talking about parameters for Gurobi optimizers and discussing how to find good parameter settings that improve performance and robustness to solve hard optimization problems.
Models with numerical issues can lead to undesirable results: slow performance, wrong answers or inconsistent behavior. When solving a model with numerical issues, tiny changes in the model or computer can make a big difference in the results. In this 45-minute webinar, given by Gurobi Sr. Developer, Dr. Daniel Espinoza, you will learn about Gurobi guidelines on numerical issues, how they impact your solutions and, most importantly, how to avoid them.
Speed is key for most users that embed Gurobi into their own application infrastructure. Input data is transformed into high quality planning solutions and results need to be delivered in a timely manner as part of a robust and reliable system architecture. Slow performance of optimization models can in some cases be solved with parameter tuning. However, during the design and the implementation of optimization systems, there are lots of other opportunities for tuning. In this 50-minute long webinar, given by Gurobi Technical Account Manager Dr. Kostja Siefen, you will learn how to maximize Gurobi’s performance and discover the most important aspects of performance tuning.
This webinar introduces Gurobi's capabilities relating to parallel and distributed optimization, provides insight into when distributed optimization is useful and also provides a performance comparison both between using parallel and distribution optimization and between using fewer machines with more cores and more machines with fewer cores. This video is also available in Deutsch.
Developing optimization solutions often requires rapid deployment to users in order to take full advantage of the capabilities. Opalytics has developed a cloud platform that provides an easy-to-use user interface and powerful deployment capabilities for optimization models. It also provides a schema wrapper for Gurobi using Python APIs that makes it easy to deploy on the platform and therefore enables fast end-to-end custom optimization development. Dr. David Simchi-Levi will show one example - Network Risk Optimization based on work he did with Ford, that won the 2014 Daniel H. Wagner Prize for Excellence in Operations Research Practice.
Algebraic modeling languages like AMPL can be a quick and effective way to build optimization applications. In this one-hour webinar you'll learn: 1) how AMPL helps you to streamline the cycle of model formulation and testing, 2) how a simple AMPL model evolves to address more complex and realistic concerns, and 3) how the AMPL system helps you embed optimization into larger applications for deployment to users.
Excel is still the most widely used tool for strategic, tactical and operational purposes in companies around the world. However, many companies run into situations where they want better decisions with less work and in less time, but don’t necessarily have the internal OR expertise to build their own enterprise-ready optimization applications. This webinar provides tips on when to migrate, how to do so successfully, and on managing optimization projects.
For those already familiar with machine learning, this webinar will share some insights on how to better leverage the output of those techniques to improve overall decision-making. For those familiar with optimization, this webinar provides an introduction on how machine learning can improve inputs to and decisions from your optimization models.
When you begin considering predictive analytics approaches along with your optimization models, you can often increase the speed at which you are solving models, incorporate more realistic data parameters and even amp up your time series data analysis inputs. Join us for an hour-long technical webinar with Gurobi and Opex Analytics to dive even deeper into the value of predictive analytics applications along side optimization models using a real-world transportation case study.
Scheduling problems arise in a wide-range of applications that require finding the best possible sequence to perform a set of tasks, including job shop scheduling and flight scheduling. This 40-minute video goes over Gurobi features that increase performance for optimal scheduling, tips on problem formulation, and implementation and tuning tricks for scheduling problems.