Category Archives: Decision Optimization

Decision Optimization Technologies

2019 Survey of Software for Linear Programming

Prof. Robert Fourer, who will be our presenter at DecisionCAMP-2019, just published the results of the 2019 Linear Programming (LP) Survey.  LP software can be very effectively used for Decision Optimization problems which deal with minimizing or maximizing business objectives subject … Continue reading

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Optimization and Machine Learning with Excel Online

Frontline Systems has released Analytic Solver® V2019, a SaaS (software as a service) cloud and desktop platform that offers Excel-savvy business analysts point-and-click tools to create predictive and prescriptive analytics models themselves, without needing expert data scientists or programmers. Both … Continue reading

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CP-2019 Workshop on Progress Towards the Holy Grail

In 1997 in the paper “In Pursuit of the Holy Grail” Prof. Gene Freuder proposed that Constraint Programming was well-positioned to pursue the Holy Grail of computer science: the user simply states the problem and the computer solves it.  Twenty … Continue reading

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Java Solver: Modeling and Solving Decision Optimization Problems

Dr. Jacob Feldman announced availability of a new open source product “Java Solver” that provides a very simple API for modeling and solving optimization problems in Java. This is probably the simplest API for adding optimization components to business decisioning … Continue reading

Posted in Decision Modeling, Decision Optimization, Products, Scheduling and Resource Allocation | Leave a comment

Similarity in Machine and Human Decision Making

In his new post “Artificial and Human Intelligence” Alain Chabrier from IBM describes decisions the members of his own  family make while packing for vacation. In simple terms Alain nicely explains how we use 3 major Decision Management techniques (Rules, … Continue reading

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Explaining Decision Optimization Recommendations

Explainability is a hot topic. Decision models are used to trigger recommendations such as “accept” or “refuse” a loan, but they also need to explain WHY they recommended certain decisions. Alain Chabrier from IBM DecisionOptimization team uses Portfolion Allocation problem … Continue reading

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Modeling and Solving Scheduling Problems with CP Optimizer

The Resource-Constrained Project Scheduling Problem (RCPSP) is a classical problem among the myriad scheduling problems studied both in academia and in industry. Philippe Laborie, a principal scientist at IBM, describes how it can easily be modeled and efficiently solved using … Continue reading

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Giving Algorithms a Sense of Uncertainty

MIT Technology Review published this article Giving algorithms a sense of uncertainty could make them more ethical: “Algorithms are built to pursue a single mathematical goal, such as maximizing the number of soldiers’ lives saved or minimizing the number of … Continue reading

Posted in Artificial Intelligence, Decision Making, Decision Optimization | 1 Comment

“Old” AI vs Deep Learning

Vincent Gosselin from DecisionBrain wrote: “At last an article that takes a realistic view of AI rather than a sole focus on deep learning. We recently came across a failed AI project where a fairly hyped company, let’s call it … Continue reading

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Finding Optimal Locations of New Store using Decision Optimization

Vincent Beraudier, IBM, in his notebook describes how to model and solve the following business problem: “A fictional Coffee Company plans to open N shops in the near future and needs to determine where they should be located knowing that … Continue reading

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