Optimization Direct at INFORMS 2022 ANNUAL MEETING, Indianapolis IN, October 16-19, 2022

We are holding technology tutorials and workshops at INFORMS Technology Tutorial at INFORMS ODH Python Primer Presented by: Robert Ashford Monday, October 17, 11:40am-12:15pm   This short tutorial shows participants how to build a basic model using the ODH|CPLEX in Python. This session includes setting the Python environment, reading data from a csv or spreadsheet,…

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REDISTRICTING WITH OPTIMIZATION

Political redistricting through mathematical optimization.

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FAIR AND ECONOMICAL REDISTRICTING THROUGH MATHEMATICAL OPTIMIZATION NOW POSSIBLE

Political redistricting can now be completed quickly, fairly and economically through mathematical optimization.

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ODH-CPLEX SOLVER IN AIMMS PLATFORM

A webinar featuring Optimization Direct Experts. In Partnership with AIMMS. Replay now available.

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COMBINING MACHINE LEARNING AND MATHEMATICAL OPTIMIZATION – Part 5

Article five of five In our first article we identified four scenarios where Machine Learning can cooperate with Mathematical Optimization. Here we identify further reading of two notable resources that can help us learn more about this topic. We encourage practitioners to review these two articles. Machine learning for combinatorial optimization: A methodological tour d’horizon…

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COMBINING MACHINE LEARNING AND MATHEMATICAL OPTIMIZATION – Part 4

Article four of five In our first article we identified four scenarios where Machine Learning can cooperate with Mathematical Optimization. In this article, we will consider Scenario D which is defined as follows: ML can be used to help MOPT solvers to perform better not only for finding solutions faster but for finding more good…

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COMBINING MACHINE LEARNING AND MATHEMATICAL OPTIMIZATION – Part 3

Article three of five In our first article we identified four scenarios where Machine Learning can cooperate with Mathematical Optimization. In this article, we will consider Scenario A and present an example. Scenario A is defined as: ‘The output of ML is input to MOPT.’ This scenario is defined as: Machine learning algorithms calculate the…

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COMBINING MACHINE LEARNING AND MATHEMATICAL OPTIMIZATION – Part 2

Article two of five Alkiviadis Vazacopoulos In our first article we identified four scenarios where Machine Learning can cooperate with Mathematical Optimization. In this article, we will consider Scenario D and present promising results from a real-world application. This scenario is defined as: ML can be used to help MOPT solvers to perform better not…

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COMBINING MACHINE LEARNING AND MATHEMATICAL OPTIMIZATION – Part 1

Article one of five Python is a widely used high-level programming language for general-purpose programming, it is designed to be straightforward to implement. Apart from being open source programming language, Python is a great object-oriented, interpreted, and interactive programming language. It combines remarkable power with noticeably clear syntax. There are modules, classes, exceptions, very high-level…

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OPTIMIZE HEALTHCARE DELIVERY AND REDUCE COSTS WITH PRESCRIPTIVE ANALYTICS

Article by Sajan Kuttappa on the IBM Big Data and Analytics hub

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OPTIMIZATION GITHUB

A GitHub repository of models, samples, data sources and libraries for decision optimization from IBM

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IBM BLOG

Why prescriptive analytics and decision optimization are crucial

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OPTIMIZATION DIRECT AT INFORMS 2020 BUSINESS ANALYTICS CONFERENCE, DENVER CO, 26-28 APRIL, 2020

We are holding technology tutorials and workshops at INFORMS

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OPTIMIZATION DIRECT MARKET IBM DECISION OPTIMIZATION CENTER

IBM DOC V4.0 now available from Optimization Direct

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AMAZING RESULTS FROM ODH|CPLEX

Results of tests on Miplib Open-v7 Models now out

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