Altering the Granularity of Neutrality in a Multi-layered Genetic Algorithm

Seamus Hill, Colm O’Riordan

Abstract

By adopting a basic interpretation of the biological processes of transcription and translation, the multilayered GA (MGA) introduces a genotype-phenotype mapping for a haploid genotype, which allows the granularity of the representation to be tuned. The paper examines the impact of altering the level of neutrality through changes in the granularity of the representation and compares the performance of a standard GA (SGA) to that of a number of multi-layered GAs, each with a different level of neutrality, over both static and changing environments. Initial results indicate that it appears advantageous to include a multi-layered, biologically motivated genotype-phenotype encoding over more difficult landscapes. The paper also introduces an interpretation of missense mutation, which operates within the genotype-phenotype map (GP-map). Results also suggest that this mutation strategy can assist in tracking the optimum over various landscapes.

References

  1. Goldberg, D. E., Korb, B., and Deb, K. (1990). Messy genetic algorithms: Motivation, analysis, and first results. Complex Systems, 3(5):493-530.
  2. Goldberg, D. E. and Smith, R. E. (1987). Nonstationary function optimization using genetic algorithm with dominance and diploidy. In Proceedings of the 2nd International Conf. on Genetic Algorithms on Genetic Algorithms and Their Application, pages 59-68, Hillsdale, NJ, USA. L. Erlbaum Associates Inc.
  3. Grefenstette, J. J. and Cobb, H. G. (1993). Genetic algorithms for tracking changing environments. In Proc. of the 5th Int. Conf. on Genetic Algorithms and their Applications, pages 523-530. Morgan Kaufmann.
  4. Hill, S. and O'Riordan, C. (2011). Examining the use of a non-trivial fixed genotype-phenotype mapping in genetic algorithms to induce phenotypic variability over deceptive uncertain landscapes. In Proceedings of the 2011 Congress of Evolutionary Computation (CEC 2011). New Orleans, USA.
  5. Kubalik, J. (2005). Using genetic algorithms with realcoded binary representation for solving non-stationary problems. In Ribeiro, B., Albrecht, R. F., Dobnikar, A., Pearson, D. W., and Steele, N., editors, Adaptive and Natural Computing Algorithms, pages 222-225. Springer Vienna.
  6. Morrison, R. W. and DeJong, K. A. (2002). Measurement of population diversity. In In 5th International Conference EA, 2001, volume 2310 of Incs. Springer.
  7. Whitley, L. D. (1991). Fundamental principles of deception in genetic search. In Rawlins, G. J., editor, Foundations of genetic algorithms, pages 221-241. Morgan Kaufmann, San Mateo, CA.
  8. Yang, S. (2006). On the design of diploid genetic algorithms for problem optimization in dynamic environments. In Evolutionary Computation, 2006. CEC 2006. IEEE Congress on, pages 1362-1369. 1000 2000 300G0enerations4000 6000 7000
  9. Figure 29: Thirty 3-Bit Deceptive Problem - SGA - Increased Mutation.
Download


Paper Citation


in Harvard Style

Hill S. and O’Riordan C. (2014). Altering the Granularity of Neutrality in a Multi-layered Genetic Algorithm . In Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014) ISBN 978-989-758-052-9, pages 215-222. DOI: 10.5220/0005072302150222


in Bibtex Style

@conference{ecta14,
author={Seamus Hill and Colm O’Riordan},
title={Altering the Granularity of Neutrality in a Multi-layered Genetic Algorithm},
booktitle={Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)},
year={2014},
pages={215-222},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005072302150222},
isbn={978-989-758-052-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation Theory and Applications - Volume 1: ECTA, (IJCCI 2014)
TI - Altering the Granularity of Neutrality in a Multi-layered Genetic Algorithm
SN - 978-989-758-052-9
AU - Hill S.
AU - O’Riordan C.
PY - 2014
SP - 215
EP - 222
DO - 10.5220/0005072302150222