Abstract
Most successful applications of Evolutionary Algorithms to real world problems employ some sort of hybridization, thus speeding up the optimization process but turning the general applicable Evolutionary Algorithm into a problem-specific tool. This paper proposes to combine Evolutionary Algorithms and generally applicable local searchers to get the best of both approaches: A fast, but robust tool for global optimization. The approach consists of four different kinds of hybridization and combinations thereof, which are tested and compared using five commonly used benchmark functions and three real world applications. The results show the superiority of two hybridization types, with which reductions in the number evaluations of up to a factor of 100 could be achieved.
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References
Holland, H. J.: Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)
Goldberg, D. E, Voessner, S.: Optimizing Global-Local Search Hybrids. In: W. Banzhaf et al. (eds.): Proc. GECCO’99, Morgan Kaufmann, San Mateo, CA (1999) 220–228
Whitley, D., Gordon, V., Mathias, K.: Lamarckian Evolution, The Baldwin Effect and Funct. Opt. In: Davidor, Y. et al.: Proc. PPSN III, LNCS 866, Springer, Berlin (1994) 6–14
Gruau, F., Whitley, D.: Adding Learning to the Cellular Development of Neural Networks: Evolution and the Baldwin Effect. Evol. Comp. 1, Vol.3 (1993) 213–233
Orvosh, D., Davis, L.: Shall We Repair? Genetic Algorithms, Combinatorial Optimization, and Feasibility Constraints. In: Forrest, S. (ed): 5th ICGA, M. Kaufmann (1993) 650
Jakob, W., Quinte, A., et al.: Opt. of a Micro Fluidic Component Using a Parallel EA and Simulation Based on Discrete Element Methods. In: Hernandez, S., et al.: Computer Aided Design of Structures VII, Proc. of OPTI’01, WIT Press, Southampton (2001) 337–346
Blume, C.: GLEAM—A System for Intuitive Learning. In: Schwefel, H. P., Männer, R. (eds.): Proc. of PPSN I, LNCS 496, Springer, Berlin (1990) 48–54
Blume, C., Jakob, W.: GLEAM—an Evolutionary Algorithm for Planning and Control Based on Evolution Strategy. Conf. Proc. GECCO 2002, Vol. Late Breaking Papers, (2002)
Jakob, W.: HyGLEAM: Hybrid GeneraL-purpose Evolutionary Algorithm and Method. In: Callaos, N. et al. (eds.): Proc. SCI’2001, Vol. III, IIIS, Orlando, (2001) 187–192
Rosenbrock, H. H.: An Automatic Method for Finding the Greatest or Least Value of a Function. Comp. Journal 3 (1960) 175–184
Box, M. J.: A New Method of Constrained Optimization and a Comparison with Other Methods. Comp. Journal 8 (1965) 42–52
Schwefel, H.-P.: Evolution and Optimum Seeking. John Wiley & Sons, Chichester (1995)
Bäck, T.: GENEsYs 1.0, ftp://lumpi.informatik.uni-dortmund.de/pub/GA
Gorges-Schleuter, M., Jakob, W., Sieber, I.: Evolutionary Design Optimization of a Microoptical Collimation System. In: Zimmermann, H. J. (ed.): Proc. Eufit’98, Verlag Mainz, Aachen (1998) 392–396
Blume, C., Jakob, W.: Cutting Down Production Costs by a New Optimization Method. In: Proc. of Japan-USA Symposium on Flexible Automation. ASME (1994)
Beyer, H.-G., et al.: Evolutionary Algorithms—Terms and Definitions. VDI/VDE-Richtlinie-3550, Blatt 3, Gründruck (Engl. vers. to be published in 2002). VDI, Düsseldorf (2001)
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Jakob, W. (2002). HyGLEAM–An Approach to Generally Applicable Hybridization of Evolutionary Algorithms. In: Guervós, J.J.M., Adamidis, P., Beyer, HG., Schwefel, HP., Fernández-Villacañas, JL. (eds) Parallel Problem Solving from Nature — PPSN VII. PPSN 2002. Lecture Notes in Computer Science, vol 2439. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45712-7_51
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DOI: https://doi.org/10.1007/3-540-45712-7_51
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