Abstract
All Evolutionary Algorithms experienced practitioners emphasiz the need for a careful design of the fitness function. It is commonly heard, for instance, that “If there is a bug in your fitness function, the EA will find it”. This paper presents a case study of such a situation in the domain of geophysical underground identification: some weird solutions are found by the Evolutionary Algorithm, obviously physically absurd, but fulfilling almost perfectly the geophysical criterion.
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References
J. Antonisse. A new interpretation of schema notation that overturns the binary encoding constraint. In J. D. Schaffer, editor, Proceedings of the 3 rd International Conference on Genetic algorithms, pages 86–91. Morgan Kaufmann, June 1989.
D.L. Battle and M.D. Vose. Isomorphisms of genetic algorithms. In G. J. E. Rawlins, editor, Foundations of Genetic Algorithms, pages 242–251. Morgan Kaufmann, 1991.
F. Boschetti. Application of genetic algorithms to the inversion of geophysical data. PhD thesis, University of Western Australia, 1995.
P. Docherty, R. Silva, S. Singh, Z. Song, and M. Wood. Migration velocity analysis using a genetic algorithm. Geophysical Prospecting, 45:865–878, 1997.
D.B. Fogel and L.C. Stayton. On the effectiveness of crossover in simulated evolutionary optimization, BioSystems, 32:171–182, 1994.
D. E. Goldberg, A theory of virtual alphabets. In Hans-Paul Schwefel and Reinhard Männer, editors, Proceedings of the 1 st Parallel Problem Solving from Nature, pages 13–22, 1991.
J. J. Grefenstette. Optimization of control parameters for genetic algorithms. IEEE Trans. on Systems, Man and Cybernetics, SMC-16, 1986.
R. Hinterding, Z. Michalewicz, and A. E. Eiben. Adaptation in evolutionary computation: A survey. In Proceedings of the 4 th IEEE International Conference on Evolutionary Computation, pages 65–69. IEEE Press, 1997.
C. Z. Janikow and Z. Michalewicz. An experimental comparison of binary and floating point representations in genetic algorithms. In R. K. Belew and L. B. Booker, editors, Proceedings of the 4 th International Conference on Genetic Algorithms, pages 31–36. Morgan Kaufmann, 1991.
S. Jin and P. Madariaga. Background velocity inversion with a genetic algorithm. Geophysical research letters, 20(2):93–96, 1993.
T. Jones. Crossover, macromutation and population-based search. In L. J. Eshelman, editor, Proceedings of the 6 th International Conference on Genetic Algorithms, pages 73–80. Morgan Kaufmann, 1995.
L. Kallel and M. Schoenauer. Alternative random initialization in genetic algorithms. In Th. Bäck, editor, Proceedings of the 7 th International Conference on Genetic Algorithms, pages 268–275. Morgan Kaufmann, 1997.
F. Mansanne. PhD thesis, Université de Pau, In preparation.
Z. Michalewicz and M. Schoenauer, Evolutionary Algorithms for Constrained Parameter Optimization Problems, Evolutionary Computation, 4(1):1–32, 1996.
F. P. Preparata and M. I. Shanos. Computational Geometry: an introduction. Springer Verlag, 1985.
J. D. Schaffer, R. A. Caruana, L. Eshelman, and R. Das. A study of control parameters affecting on-line performance of genetic algorithms for function optimization. In J. D. Schaffer, editor, Proceedings of the 3 rd International Conference on Genetic Algorithms, pages 51–60. Morgan Kaufmann, 1989.
M. Schoenauer. Representations for evolutionary optimization and identification in structural mechanics. In J. Périaux and G. Winter, editors, Genetic Algorithms in Engineering and Computer Sciences, pages 443–464. John Wiley, 1995.
M. Schoenauer, A. Ehinger, and B. Braunschweig. Non-parametric identification of geological models. In Proceedings of the 5 th IEEE International Conference on Evolutionary Computation. IEEE Press, 1998.
M. Schoenauer, L. Kallel and F. Jouve, Mechanical inclusions identification by evolutionary computation. European J. of Finite Elements, 5 (5–6):619–648, 1996.
H.-P. Schwefel, Numerical Optimization of Computer Models. John Wiley & Sons, New-York, 1981, 1995—2nd edition.
P.L. Stoffa and M.K. Sen. Nonlinear multiparameter optimization using genetic algorithms: inversion of plane-wave seismograms. Geophysics, 56, 1991.
P.D. Surry and N.J. Radcliffe. Formal algorithms+formal representations=search strategies. In H.-M. Voigt et al., editors, Proceedings of the 4 th Parallel Problems Solving from Nature, pages 366–375. Springer Verlag, 1996.
P.D. Surry and N.J. Radcliffe. Inoculation to initialise evolutionary search. In AISB Evolutionary Computing. LNCS 1141, pages 269–285. Springer Verlag, 1996.
M.T. Taner and F. Koehler. Velocity spectra-digital computer derivation and applications to velocity functions. Geophysics, 56:1794–1810, 1969.
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Mansanne, F., Carrère, F., Ehinger, A., Schoenauer, M. (1999). Evolutionary Algorithms as fitness function debuggers. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1999. Lecture Notes in Computer Science, vol 1609. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095153
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DOI: https://doi.org/10.1007/BFb0095153
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