【中文网络讲座】Gurobi 10.0 发布 -- 新亮点和技术创新
本次网络讲座中，Gurobi Optimization 公司的 CTO 和创始人顾宗浩博士将会介绍Gurobi 10.0 的新亮点和技术创新。讲座内容包括性能提升采用的新技术和新算法，例如网络单纯形算法，并发LP 求解算法的改进和基于优化的边界紧缩技术OBBT等。Gurobi 10.0将是第一个允许将用户的机器学习模型嵌入到数学规划模型中的商业求解器，极大括展了数据科学家调用运筹算法的能力，这部分功能在Github上开源提供。这部分内容也会在讲座中介绍，以及其他一些开源的效率工具，例如对 pandas 数据的建模支持等。
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ML and Optimization to determine best store network
BearingPoint has been using analytics to support its supply chain projects for many years. Optimisation is a key tool, especially for network optimisation projects, but typically would be combined with other analytical methods.
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New Directions for Optimization
In this video, learn about the motivation for some of the recent features added to the Gurobi Optimizer as well as recent developments in the field and how they are influencing our thinking on potential future directions.
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Using the Automatic Parameter Tuning Tool
This 17 minute video seminar explains the importance of parameters and how to use the Automatic Parameter Tuning Tool to help you maximize Gurobi’s performance.
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Non-Convex Quadratic Optimization
With the release of Gurobi 9.0’s addition of a new bilinear solver, the Gurobi Optimizer now supports non-convex quadratic optimization. This groundbreaking new capability allows users to solve problems with non-convex quadratic constraints and objectives – enabling them to find globally optimal solutions to classic bilinear pooling and blending problems and continuous manufacturing problems.
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How Optimization Modeling Creates Value for an Organization
Learn how to better showcase the value of optimization in your organization.
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Combining Optimization with Machine Learning Webinar, Part 1
Combining Optimization with Machine Learning for Better Decisions.
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Enabling Client-Server Optimization Applications With the New Gurobi Compute Server
This one hour video seminar explains how you can enable Client-Server optimization applications with the new Gurobi Compute Server.
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Non-Convex Quadratic Optimization
This video shows one of the major new feature in Gurobi 9.0, the new bilinear solver, which allows users to solve problems with non-convex quadratic objectives and constraints such as QPs, QCPs, MIQPs, and MIQCPs.
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Intro to Performance Tuning for Optimization Systems with Gurobi
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.
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