ABSTRACT
A new speciation method for parallel evolutionary computation is presented, designed specifically to handle high-dimensional data. Taking inspiration from the natural sciences, the Phylogenetic Relations Island Speciation Model (PRISM) uses common ancestry and a novel species barcoding system to detect new species and move them to separate islands. Simulation experiments were performed on Multidimensional Knapsack Problems with different fitness landscapes requiring 100-dimensional genomes. PRISM's performance with various parameter settings and on the various landscapes is analyzed and preliminary results show that PRISM can consistently produce optimal or near-optimal solutions, outperforming the standard Genetic Algorithm and Island Model in all the performed experiments.
- M. Bessaou, A. Pétrowski, and P. Siarry. Island model cooperating with speciation for multimodal optimization. In PPSN VI: Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, pages 437--446, London, UK, 2000. Springer-Verlag. Google ScholarDigital Library
- K.S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is "nearest neighbor" meaningful? In ICDT '99: Proceeding of the 7th International Conference on Database Theory, pages 217--235, London, UK, 1999. Springer-Verlag. Google ScholarDigital Library
- P.C. Chu and J.E. Beasley. A genetic algorithm for the multidimensional knapsack problem. Journal of Heuristics, 4(1):63--86, 1998. Google ScholarDigital Library
- J.P. Cohoon, S.U. Hegde, W.N. Martin, and D. Richards. Punctuated equilibria: a parallel genetic algorithm. In Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application, pages 148--154, Hillsdale, NJ, USA, 1987. L. Erlbaum Associates Inc. Google ScholarDigital Library
- C. Ding, X. He, H. Zha, and H.D. Simon. Adaptive dimension reduction for clustering high dimensional data. In ICDM '02: Proceedings of the 2002 IEEE International Conference on Data Mining (ICDM'02), pages 147--154, Washington, DC, USA, 2002. IEEE Computer Society. Google ScholarDigital Library
- M.J. Donoghue. A critique of the biological species concept and recommendations for a phylogenetic alternative. Bryologist, 88(3):171--181, Fall 1985 1985.Google ScholarCross Ref
- A. Freville. The multidimensional 0-1 knapsack problem: An overview. European Journal of Operational Research, 155(1):1--21, May 2004.Google ScholarCross Ref
- S. Gustafson and E.K. Burke. The speciating island model: an alternative parallel evolutionary algorithm. Parallel and Distributed Computing, 66(8):1025--1036, 2006. Google ScholarDigital Library
- S. Gustafson, E.K. Burke, and N. Krasnogor. The treestring problem: An artificial domain for structure and content search. In Genetic Programming, Proceedings of the 6th European Conference, volume 3447 of LNCS, pages 215--226. Springer-Verlag, 2005. Google ScholarDigital Library
- P.D.N. Hebert, A. Cywinska, S.L. Ball, and J.R. Dewaard. Biological identifications through dna barcodes. Proceedings of the Royal Society B: Biological Sciences, 270(1512):313--321, February 2003.Google ScholarCross Ref
- J.H. Holland. Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI, USA, 1975. Google ScholarDigital Library
- J.-P. Li, M.E. Balazs, G.T. Parks, and P.J. Clarkson. A species conserving genetic algorithm for multimodal function optimization. Evolutionary Computation, 10(3):207--234, 2002. Google ScholarDigital Library
- A.F.K. Morales and J. Gutiérrez-Garc1a. Penalty function methods for constrained optimization with genetic algorithms: A statistical analysis. In MICAI'02: Proceedings of the Second Mexican International Conference on Artificial Intelligence, pages 108--117, London, UK, 2002. Springer-Verlag. Google ScholarDigital Library
- A. Petrowski and M.G. Genet. A classification tree for speciation. In In Proceedings of CEC 1999, pages 204--211. IEEE Press, 1999.Google ScholarCross Ref
- Z. Skolicki and K.D. Jong. The influence of migration sizes and intervals on island models. In GECCO '05: Proceedings of the 2005 conference on Genetic and evolutionary computation, pages 1295--1302, New York, NY, USA, 2005. ACM. Google ScholarDigital Library
- S. Via. Sympatric speciation in animals: the ugly duckling grows up. Trends in Ecology and Evolution, 16(7):381--390, July 2001.Google ScholarCross Ref
- Y. Yang, J. Vincent, and G. Littlefair. A coarse-grained parallel genetic algorithm employing cluster analysis for multi-modal numerical optimisation. In Artificial Evolution, pages 229--240, 2003.Google Scholar
Index Terms
- An island model for high-dimensional genomes using phylogenetic speciation and species barcoding
Recommendations
Analysis of evolutionary multi-tasking as an island model
GECCO '18: Proceedings of the Genetic and Evolutionary Computation Conference CompanionRecently, an idea of evolutionary multi-tasking has been proposed and applied to various types of optimization problems. The basic idea of evolutionary multi-tasking is to simultaneously solve multiple optimization problems (i.e., tasks) in a ...
Analysis of speedups in parallel evolutionary algorithms and ( 1 + λ ) EAs for combinatorial optimization
Evolutionary algorithms are popular heuristics for solving various combinatorial problems as they are easy to apply and often produce good results. Island models parallelize evolution by using different populations, called islands, which are connected ...
The speciating island model: an alternative parallel evolutionary algorithm
Special issue on parallel bioinspired algorithmsThis paper presents an investigation of a novel model for parallel evolutionary algorithms (EAs) based on the biological concept of species. In EA population search, new species represent solutions that could lead to good solutions but are disadvantaged ...
Comments