PURE CO-EVOLUTION FOR SHAPE NESTING

Jeffrey Horn

Abstract

We test the effectiveness of an evolutionary algorithm that relies completely on species selection for evolution and on interactions among species to determine fitness. Under Resource-defined Fitness Sharing (RFS), all individuals have the same objective fitness, but they act to reduce their shared fitness through competition for resources. In previous studies, RFS has been used to evolve populations of mutually non-competing (i.e., non-overlapping) shapes on shape nesting problems. In this paper we test the effectiveness of a modified version of RFS, which we call PCSN, against three commercial software packages for shape nesting. PCSN uses species proportions to represent a population, thereby simulating an infinitely large population. With no discovery operators, such as mutation or recombination, evolution consists of selection only, with all species present in the initial population. We show that on some shape nesting problems this approach can outperform some commercial packages. In particular, PCSN nests more circles on a fixed, polygonal substrate than do most of the commercial packages. This might be considered a surprising result, since the algorithm is radically different from any shape nesting algorithms deployed to date. While conventional methods place one shape at a time, the co-evolution approach attempts to place all shapes simultaneously.

References

  1. Dighe, R., Jakiela, M. J., 1996. Solving Pattern Nesting Problems with Genetic Algorithms: Employing Task Decomposition and Contact Detection Between Adjacent Pieces. Evolutionary Computation, 3, 239- 266.
  2. Goldberg, D. E., Richardson, J., 1987. Genetic algorithms with sharing for multi-modal function optimization. In Grefenstette, J. (Ed.), Proceedings of the Second International Conference on Genetic Algorithms pages (pp. 41-49). Hillsdale, NJ: L. Erlbaum Associates.
  3. Horn, J., 2002. Resource-based fitness sharing. In Guervós, J. J. M., Adamidis, P., Beyer, H.-G., Martín, J. L. F.-V., and Schwefel, H.-P. (Ed.s), Parallel Problem Solving From Nature (PPSN VII, Lecture Notes in Computer Science, Vol. 2439, pp. 381-390). Berlin/Heidelberg: Springer.
  4. Horn, J., 2005. Coevolving species for shape nesting. In Schaeffer, J. D. (Ed.), The 2005 IEEE Congress on Evolutionary Computation (IEEE CEC 2005, pp. 1800-1807). Piscataway, NJ: IEEE Press.
  5. Horn, J., 2008. Optimal nesting of species for exact cover of resources: many against many. In Rudolph, G., Jansen, T., Lucas, S., Poloni, C. and Beume, N. (Ed.s), Parallel Problem Solving From Nature X (PPSN X, Lecture Notes in Computer, Vol. 5199, pp. 438-448). Berlin/Heidelberg: Springer.
  6. Kendall, G., 2000. Applying Meta-Heuristic Algorithms to the Nesting Problem Utilising the No Fit Polygon. Ph.D. thesis, University of Nottingham.
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Paper Citation


in Harvard Style

Horn J. (2010). PURE CO-EVOLUTION FOR SHAPE NESTING . In Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010) ISBN 978-989-8425-31-7, pages 255-260. DOI: 10.5220/0003089402550260


in Bibtex Style

@conference{icec10,
author={Jeffrey Horn},
title={PURE CO-EVOLUTION FOR SHAPE NESTING},
booktitle={Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)},
year={2010},
pages={255-260},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003089402550260},
isbn={978-989-8425-31-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)
TI - PURE CO-EVOLUTION FOR SHAPE NESTING
SN - 978-989-8425-31-7
AU - Horn J.
PY - 2010
SP - 255
EP - 260
DO - 10.5220/0003089402550260