CISUC

Evolving Evolutionary Algorithms

Authors

Abstract

This paper proposes a Grammatical Evolution framework to the automatic design of Evolutionary Algorithms. We define a grammar that has the ability to combine components regularly appearing in existing evolutionary algorithms, aiming to achieve novel and fully functional optimization methods. The problem of the Royal Road Functions is used to assess the capacity of the framework to evolve algorithms. Results show that the computational system is able to evolve simple evolutionary algorithms that can effectively solve Royal Road instances. Moreover, some unusual design solutions, competitive with standard approaches, are also proposed by the grammatical evolution framework.

Keywords

Evolutionary Algorithms, Hyper-heurisitics, Automatic Evolution

Conference

Genetic and Evolutionary Computation Conference (GECCO-2012), July 2012

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Cited by

Year 2016 : 6 citations

 van Rijn, Sander, Hao Wang, Matthijs van Leeuwen, and Thomas Bäck. "Evolving the Structure of Evolution Strategies." arXiv preprint arXiv:1610.05231 (2016)

 Franzin, Alberto, and Thomas Stützle. "Exploration of Metaheuristics through Automatic Algorithm Configuration Techniques and Algorithmic Frameworks." Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion. ACM, 2016.

 Mariani, Thainá, Giovani Guizzo, Silvia R. Vergilio, and Aurora TR Pozo. "A grammatical evolution hyper-heuristic for the integration and test order problem." GECCO. ACM, 2016.

 Mariani, Thainá, Giovani Guizzo, Silvia R. Vergilio, and Aurora TR Pozo. "Grammatical Evolution for the Multi-Objective Integration and Test Order Problem." Proceedings of the 2016 on Genetic and Evolutionary Computation Conference. ACM, 2016.

 Harris, Sean, Travis Bueter, and Daniel R. Tauritz. "A Comparison of Genetic Programming Variants for Hyper-Heuristics." Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation. ACM, 2015.

 Martin, Matthew A., and Daniel R. Tauritz. "Hyper-Heuristics: A Study On Increasing Primitive-Space." Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation. ACM, 2015.

Year 2015 : 4 citations

 Ryser-Welch, Patricia, Julian F. Miller, and Shahriar Asta. "Generating human-readable algorithms for the Travelling Salesman Problem using Hyper-Heuristics." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.

 Ryser-Welch, Patricia, Julian F. Miller, and Shariar Asta. "Evolutionary Cross-Domain Hyper-Heuristics." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.

 Aboshosha, Ashraf, Kamal A. ElDahshan, Eman K. Elsayed, and Ahmed A. Elngar. "EA Based Dynamic Key Generation in RC4 Ciphering Applied to CMS."

 Martin, Matthew A., and Daniel R. Tauritz. "Hyper-Heuristics: A Study On Increasing Primitive-Space." Proceedings of the Companion Publication of the 2015 on Genetic and Evolutionary Computation Conference. ACM, 2015.

Year 2014 : 2 citations

 Ryser-Welch, Patricia, and Julian F. Miller. "A Review of Hyper-Heuristic Frameworks.", Proceedings of the 50th Anniversary Convention of the AISB

 Martin, Matthew A., and Daniel R. Tauritz, "A problem configuration study of the robustness of a black-box search algorithm hyper-heuristic", Proceedings of the 2014 conference companion on Genetic and evolutionary computation companion. ACM, 2014

Year 2013 : 2 citations

 Martin, Matthew A., and Daniel R. Tauritz. "Evolving black-box search algorithms employing genetic programming." Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion. ACM, 2013.

 de Sá, Alex Guimarães Cardoso, and Gisele Lobo Pappa. "Towards a method for automatically evolving bayesian network classifiers." Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion. ACM, 2013.