Automatic design of algorithms for optimization problems

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Contreras-Bolton:2015:LA-CCI,

• author = "Carlos Contreras-Bolton and Victor Parada",
• booktitle = "2015 Latin America Congress on Computational Intelligence (LA-CCI)",
• title = "Automatic design of algorithms for optimization problems",
• year = "2015",
• abstract = "The design of efficient algorithms for difficult combinatorial optimisation problems remains a challenging field. Many heuristic, meta-heuristic and hyper-heuristic methods exist. In the specialized literature, it is observed that for some problems, the combined algorithms have better computational performance than individual performance. However, the automatic combination of the existing methods or the automatic design of new algorithms has received less attention in the literature. In this study, a method to automatically design algorithms is put into practice for two optimisation problems of recognised computational difficulty: the travelling salesman problem and the automatic clustering problem. The new algorithms are generated by means of genetic programming and are numerically evaluated with sets of typical instances for each problem. From an initial population of randomly generated algorithms, a systematic convergence towards the better algorithms is observed after a few hundred generations. Numerical results obtained from the evaluation of each of the designed algorithms suggest that for each set of instances with similar characteristics, specialized algorithms are required.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/LA-CCI.2015.7435977",
• month = oct,
• notes = "Also known as \cite{7435977}",

}

Genetic Programming entries for Carlos Contreras-Bolton Victor Parada

Citations