Category Archives: Optimization

Decision Optimization Technologies

Decision Optimization for Dynamic Pricing

FICO posted an interesting article “Fair Pricing with Price Optimisation”. A similar system “Using Machine Learning, Business Rules, and Optimization for Flash Sale Pricing” has been developed by OpenRules.  These examples demonstrate the power and flexibility of Decision Optimization when business rules, … Continue reading

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Solutions to Nov-2018 Challenge “Vacation Days Advanced”

We’ve already received 3 submissions with solutions to our November challenge “Vacation Days Advanced” using different tools: FICO Blaze Advisor, OpenRules, and DT5GL . Contrary to the 2016 challenge “Vacation Days”, this one doesn’t have inter-rules relationships like “apply this rule only … Continue reading

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Ten years of CP Optimizer

Paul Shaw presented a summary of ten years of evolution of CP Optimizer, one of the most powerful constraint programming engines:

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Challenge Sep-2018 “Balanced Assignment”

This challenge deals with assignment of people to certain activities, for instance: assigning students to project groups or assigning professors to offices.  We are using the problem formulation and test data provided by Prof. Robert Fourer (AMPL). We expect that not … Continue reading

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Chaining Machine Learning and Optimization Models

Machine learning is about predicting, while optimization is about solving (searching for the values of variables that lead to the best outcomes). The latest Nathan Brixius’s post discusses different ways of combining optimization and machine learning: 1. Optimization as a means … Continue reading

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Decision Automation and Explanations

Prof. Gene Freuder wrote a position paper “Complete Explanations”: “The position taken here is that it can be worthwhile to start with truly complete explanations and abstract and limit from there. The goal is to provide a high-level “big picture” of … Continue reading

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How to Optimally Allocate “Bribe” Money

Tallys Yunes published an Excel-based optimization model that calculates the likelihood that certain agents will perform a given action that benefits you. Link Below are a few examples:

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