Archive for the ‘Publications’ Category
Last week I was at EuroGP where I presented my latest paper “Automatic Design of Ant Algorithms with Grammatical Evolution” (pdf, slides) and it won the Best Paper Award! I am very happy with this distinction since EuroGP is the leading conference on Genetic Programming attended by the best researchers in the field.
In this paper, a Grammatical Evolution approach is used for the automatic design of Ant Colony Optimization algorithms. The used grammar has the ability to guide the learning of novel architectures, by rearranging components regularly found on manually designed variants (for example, the Elitist Ant-System, the Ant Colony System or the Max-Min Ant System). This approach was tested with the TSP and the results show that the evolved algorithmic strategies are effective, exhibit a good generalization capability and are competitive with human designed variants. This is still a starting point and there is a large amount of work to be done but the indications given by these results are encouraging!
This year the conference took place in Málaga, Spain, as part of Evo* as usual. The event was great with an excellent organization lead by Carlos Cotta. It was a fantastic Evo*! Next year it will be held in Wien!
Although a bit late for this post but the year started with a good news: the paper I co-authored with Salma Mesmoudi was accepted at EvoBIO 2010. So, I am going to Istanbul to attend the Evo* set of conferences and workshops. This paper results from my final time at INRIA with Salma. We are still collaborating but due to my constant movements we weren’t able to finish it sooner. Let’s see if we can continue to work on some of possibilities that are open with this work.
And for the record, our paper is titled “Variable Genetic Operator Search for the Molecular Docking Problem”, and the abstract is:
The aim of this work is to present a new hybrid algorithm for the Molecular Docking problem: Variable Genetic Operator Search (VGOS). The proposed method combines an Evolutionary Algorithm with Variable Neighborhood Search. Experimental results show that the algorithm is able to achieve good results, in terms of energy optimization and RMSD values for several molecules when compared with previous approaches. In addition, when hybridized with the L-BFGS local search method it attains very competitive results.
[UPDATE]: Just received the news that the paper was nominated for the Best Paper Award!