The Analytics Maturity Model
Analytics can be defined in many ways, but what matters is the purpose of analytics. Most definitions agree on the following: analytics is used to gain insights from data in order to make better decisions, see for instance INFORMS definition :
Analytics is defined as the scientific process of transforming data into insight for making better decisions.
Some speak of actionable insights to stress the purpose of such insights. Then, various levels of analytics maturity can be distinguished, depending on how much... [More]
Tags: optimization analytics 
Data Science Is Hard : A Look At Sotchi Olympics
Data Science is hard. I'll use an example that made lots of buzz to show some of the issues with data science. Two brothers, Dan and Tim Graettinger, who work for Discovery Corps, Inc. devised a predictive model that predicts medal count per country for the Sotchi Olympics. The Graettinger brothers model was commented on most data science and analytics sites, in OR blogs (see Laura McLay's entry) , even beyond . Question is: did they predict medal count correctly?
Before answering that question let me... [More]
Tags: data_science analytics 
Solving the hardest Sudoku  part 2
My previous post on Sudoku described how a fairly simple OPL model could be used to solve a hard Sudoku problem. I ended the post this way:
What?
What do you say?
I see, you're asking about the solution to the above Sudoku. Well, why not download CPLEX for free and run the above model to find out?
This post is a detailed tutorial on how to run that Sudoku model on a Windows PC using CPLEX. It also addresses an interesting challenge about using Microsoft Excel for defining the problem data... [More]

Solving the hardest Sudoku  part 1
Do you know the hardest Sudoku problem? Do you know the best way to solve it? Before answering these questions, let me remind you of what the Sudoku puzzle is about in case you haven't read a newspaper in the last decade (adapted from wikipedia ):
The objective is to fill a 9×9 grid with digits so that the digits in each column, each row, and each of the nine 3×3 subgrids that compose the grid (also called ""blocks") are pairwise different. The puzzle setter provides a partially completed grid,... [More]
Tags: constraint_programming mathematical_optimization optimization analytics sudoku mathematics 
Tower of Hanoi at Large
Did you know that the Tower of Hanoi puzzle had real world applications? I was lucky enough to be involved with one such application . Before describing the application, let me recap briefly what the puzzle is about. I'll borrow the definition from wikipedia .
The Tower of Hanoi (also called the Tower of Brahma or Lucas' Tower , [ 1 ] and sometimes pluralised) is a mathematical game or puzzle . It consists of three rods, and a number of disks of different sizes which can slide onto any rod. The puzzle starts with the... [More]
Tags: analytics constraint_programming smarter_city optimization 
Centers of Polygons in OPL
Ryan J. O'Neil has written an interesting post on centers of polygons . Reason I'm blogging here is that he also asks an interesting question for the case where the polygon is a rectangle. Before looking at rectangles, let's define the general problem. There are several definitions of the center of polygons, and we'll use the one used by Ryan: it is the center of the largest circle contained by the polygon. It is called the Chebyshev center of the polygon.
Here is an example used by... [More]
Tags: mathematics optimization analytics mathematical_optimization 
Constraint Programming History
Paul Shaw and I were invited by John Poppelaars to give talks at the Back to School seminar of Dutch ORMS society.
Part of our presentation was a brief history of constraint programming. We drafted this slide to summarize it.
We certainly left out many important topics and CP systems, and we welcome any suggestions to improve it. You can use comments to this post for suggested changes and additions.
Before commenting about what we missed, please have a look at the full presentation as it will provide... [More]
Tags: analytics optimization 
Free CPLEX Trials
You would like to try CPLEX before making any investment decision and don't know where to start? There is an easy way, using the free evaluation available on our developerWorks site. The evaluation period for this trial is 90 days. All of the product's features are enabled. After the trial period is over, you can get an extended evaluation . When you download this trial, you are entitled to submit technical problems and questions through our IBM Optimization forum.
Before detailing how to get... [More]
Tags: evaluation cplex analytics free 
2013
To all my readers, I hope you enjoyed reading this blog as much as I enjoyed writing it. I want to thank you all as you are the reason for the existence of the blog.
You'll find below a quick recap of the blog activity for 2013. I wish all of you a happy and fruitful 2014!
My blog got about 130,000 page views (not counting the home page) during 2013, with 31 new posts. It is a significant increase compared to the 31,000 pages views in 2012.
The number of views increased significantly very late in... [More]
Tags: optimization analytics cplex 
No, The TSP Isn't NP Complete
Two recent blog posts discussing the Traveling Saleman Problem (TSP) led me to write this post. The two blog posts are What is Operations Research by Graham Kendall, and I’ve Been Everywhere (Optimally…) by Rob Jefferson. Both are worth reading (I wish I had written them..). These posts share two interesting properties: both discuss the TSP, and both make a slight mistake about the TSP. The same mistake occurs regularly in blog posts and even books.
The... [More]
Tags: optimization analytics np 
Free CPLEX Software For Academics
Here is an update of my previous post on this topic . IBM ILOG CPLEX Optimization Studio (CPLEX) is free for for academics thanks to the IBM Academic Initiative.
IBM Academic Initiative (AI) is a global program that faculty members, research professionals at accredited institutions, and qualifying members of standards organizations can join. Members can get full versions of a large selection of IBM software, including CPLEX at no charge. More information about IBM ILOG Optimization products in the IBM... [More]
Tags: free cplex academic 
Solving Flexible Job Shop Scheduling Problems
A recent post by Quintq team about solving hard scheduling problems made me wonder how our Constraint Programming Optimizer (CP Optimizer) would perform on the same problems. I therefore contacted Philippe Laborie who is working on CP Optimizer. He worked with another colleague, Petr Vilim, and quickly produced quite interesting results using our forthcoming version 12.6 of CP Optimizer . Here is how Philippe and Petr describe what they did.
JeanFrançois Puget
This benchmark is known as... [More]
Tags: constraint_programming benchmark 
2013 INFORMS Annual Meeting Presentations
Several of my colleagues were speakers at the 2013 INFORMS Annual Meeting . I have tweeted about it and got many requests about the material.
Good news is that we have made all presented material available in our developerWorks community . You'll find the abstract and download links for the following talks and tutorial. All material is available for free.
Analyzing 12 Years of Progress in CPLEX by Roland Wunderling
CPLEX Distributed MIP by Laszlo Ladanyi and Daniel Junglas... [More]
Tags: analytics education informs optimization 
Financial Institutions Use CPLEX On Mainframe To Manage Risks And Improve Efficiency
Last year we announced the availability of our CPLEX mathematical solver on IBM mainframes called z Enterprise. Since then we have seen financial institutions use it in various ways. This article by my colleagues Aimee EmeryOrtiz, Ferenc Katai, and Sofiane Oussedik review some of these use cases.
The paper provides some insights on how CPLEX can be used on mainframe to address banking and finance IT challenges. Not only some business operations need to be optimized, but this has to be done while maintaining... [More]
Tags: analytics zenterprise 
Benchmarking Is Tricky
We benchmark all the time. Why?
There are mainly two reasons. First, our customers keep asking for performance improvements, as they apply CPLEX to larger and more complex problems. We therefore need to make sure newer releases of CPLEX are faster for our customers. The only way to know is to benchmark our code. Second, marketing people like to be able to claim speedup in their messaging. Indeed, this boils down to a simple number that can be reused everywhere. The latter is a nice side... [More]
Tags: analytics cplex benchmark 