Abstract | ||
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We are interested in methods and strategies that allow us to simplify the code of bio-inspired algorithms without altering their performance. In this paper, we study an artificial immune algorithm specially designed to solve Relaxed Traveling Tournament Problems which has been able to obtain new bounds for some instances of this problem. We use the EvoCa tuner to analyze the components of the algorithm in order to discard some parts of the code. The results show that the filtered algorithm is able to solve the instances as well as does the original algorithm, and with this code we have obtained new bounds for some instances of the problem. |
Year | DOI | Venue |
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2015 | 10.1145/2739480.2754753 | GECCO |
Keywords | DocType | Citations |
Tuning, Immune Algorithms, Code Refining | Conference | 0 |
PageRank | References | Authors |
0.34 | 14 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Elizabeth Montero | 1 | 3 | 2.05 |
María Cristina Riff | 2 | 17 | 6.72 |