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The Art of Evolutionary Algorithm Programming

Juan Julián Merelo
Professor at ETS de Ingeniería Informática.
University of Granada



This tutorial gives an holistic view of coding in science from idea to publication, introducing several mantras that can be used at every step of the process. It is language-agnostic, in the sense that it does not push a particular language, but talks about design patterns and workflows that can be used to make the process of publishing papers based on the code you write much painless. It is a set of best practices, gleaned from experience, that can be applied to pretty much everybody that is in the business of scientific programming. The tutorial will include interactive exercises the student can do on her own computer and also a demo.


1. Comments on the quality of scientific programming at large.

2. Introduction to open source and why it's important for reproductibility of science.

3. Collaborative programming: source code management and other tools.

4. Benchmarking and performance measurement.

5. Improving speed-to-publish.

6. Literate programming.


Juan Julián Merelo is professor at the University of Granada and author of the Algorithm: Evolutionary Perl module. He has been working in evolutionary algorithms since the nineties and is mainly interested in distributed evolutionary computation and, if possible, weird forms of same. Research group blog at http://geneura.wordpress.com.

He's given tutorials at past GECCO and CEC conferences and been keynote speaker at GAME-ON and AgentDays workshops. He has a PhD in Physics and also writes novels in his free time. The previous edition of the proposed tutorial was delivered in CEC 2011 in New Orleans. It would be also welcome a statement of the expected enrollment (i.e., what sort of background should the attendants have). Please notice that the tutorials are expected to have a duration of about 2 hours. It's an introductory-level tutorial, so it is in principle addressed to anybody who is involved in the field, including other metaheuristics.


The length of the tutorial:
two hours.


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