stegua.github.io
Blog Archive - Spaghetti Optimization
http://stegua.github.io/blog/archives
My cookbook about Math, Algorithms, and Programming. Exercise in Python: remove blanks from strings. Graph Coloring: Column Generation or Column Enumeration? Big Data and Convex Optimization. Posted in Big Data. The Impact of Preprocessing on the MIPLIB2003. An Informal Report from the Combinatorial Optimization Workshop @ Aussois 2014. Posted in Combinatorial Optimization. Public Transport and Big Data. The Researcher’s Bible. GeCol: a Graph Coloring solver on top of Gecode. Posted in DIMACS Challenge.
stegua.github.io
Backtrack Programming in c - Spaghetti Optimization
http://stegua.github.io/blog/2013/03/22/backtrack-programming-in-c
My cookbook about Math, Algorithms, and Programming. Backtrack Programming in C. Recently, I have discovered a nice tiny library (1 file! That supports Backtrack Programming. The library is called CBack. And is developed by Keld Helsgaun. Who is known in the Operations Research and Computer Science communities for his efficient implementation of the Lin-Kernighan heuristics for the Travelling Salesman Problem. Offers basically two functions that are described in [1] as follows:. Problem and the 15-puzzle.
stegua.github.io
Public Transport and Big Data - Spaghetti Optimization
http://stegua.github.io/blog/2013/11/17/public-transport-and-big-data
My cookbook about Math, Algorithms, and Programming. Public Transport and Big Data. A simple query for Big Data on Google gives about 26,700,000 results. Is not really a. But still on Google you can get almost the same number as with Big Data : 26,400,000 results. Why is Public Transport so important? Of us use Public Transport. Every day, but. Well, for time, it is not always true, but it happens more often than commonly perceived). Thus, an important challenge. And use Public Transport. However, new pr...
stegua.github.io
Credits - Spaghetti Optimization
http://stegua.github.io/credits
My cookbook about Math, Algorithms, and Programming. This blog was started after several discussions with my friend and coauthor Stefano Coniglio. Who always proofreads my posts. Though I have not convinced him to write a guest post yet, he is a contributor of this blog: thanks Stefano! Another friend and coauthor that supports this blog is Marco Chiarandini. I do not know how he finds the time to proofread my posts, but he does, with the same seriousness as if he were reviewing a paper: thanks Marco!
stegua.github.io
GeCol: a Graph Coloring solver on top of Gecode - Spaghetti Optimization
http://stegua.github.io/blog/2013/06/28/gecol
My cookbook about Math, Algorithms, and Programming. GeCol: A Graph Coloring Solver on Top of Gecode. This post is about solving the classical Graph Coloring. Problem by using a simple solver, named here GeCol. That is built on top of the Constraint Programming (CP) solver Gecode. The approach of GeCol is based on the CP model described in [1]. Here, we want to explore some of the new features of the last version of Gecode (version 4.0.0), namely:. Lightweight Dynamic Symmetry Breaking (LDSB). It is poss...
stegua.github.io
Reading Excuses - Spaghetti Optimization
http://stegua.github.io/blog/2013/11/01/reading-excuses
My cookbook about Math, Algorithms, and Programming. I love reading about everything and I am glad that part of my work consists in reading. Unfortunately, for researchers, reading is not always that easy, as clearly explained in The Researcher’s Bible. Stage of academic development. Reading is extremely seductive. And the situation became even worse after reading the answers to the following question raised by Michael Trick. What paper should everyone read? Posted by Stefano Gualandi. Updated Nov 1 st.
stegua.github.io
Big Data and Convex Optimization - Spaghetti Optimization
http://stegua.github.io/blog/2014/09/27/big-data-and-convex-optimization
My cookbook about Math, Algorithms, and Programming. Big Data and Convex Optimization. In the last months, I came several times across different definitions of Big Data. However, when someone asks me what Big Data means in practice, I am never able to give a satisfactory explanation. Indeed, you can easily find a flood of posts on twitter, blogs, newspaper, and even scientific journals and conferences, but I always kept feeling that Big Data. Distributed Optimization and Statistical Learning via the Alte...
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