Abstract
A new type of schema, c-schema, is introduced, which emphasizes the inner structure, particularly specific-symbol clusters rather than the defining length. A new type of building block, c-building block, is also suggested as a consequence of this. The expected survival probability of a schema based on this new schema model is given as well as a new explanation about how allelic reordering by depth first search can help improve genetic algorithms' search capability. Extensive experimental results are also provided.
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References
T. N. Bui, S. Chaudhuri, F. T. Leighton, and M. Sipser, “Graph Bisection Algorithms with Good Average Case Behavior,” Combinatorica, Vol. 7, No. 2, 1987, pp. 171–191.
T. N. Bui and B. R. Moon, “A Genetic Algorithm for a Special Class of the Quadratic Assignment Problem,” to appear in The Quadratic Assignment and Related problems, DIMACS Series in Discrete Mathematics and Theoretical Computer Science.
T. N. Bui and B. R. Moon, “Hyperplane Synthesis for Genetic Algorithms,” Proc. of the Fifth Int. Conf. on Genetic Algorithms, July 1993, pp. 102–109.
T. N. Bui and B. R. Moon, “A Fast and Stable Hybrid Genetic Algorithm for the Ratio-Cut Partitioning Problem on Hypergraphs,” Proc. of the 31st ACM/IEEE Design Automation Conference, June 1994, pp. 664–669.
T. N. Bui and B. R. Moon, “A New Genetic Approach for The Traveling Salesman Problem,” Proc. of the First IEEE Conference on Evolutionary Computation, June 1994, pp. 7–12.
D. Cavicchio, “Adaptive Search Using Simulated Evolution,” Unpublished Doctoral Dissertation, University of Michigan, 1970.
K. DeJong, An Analysis of The Behavior of A Class of Genetic Adaptive Systems, Doctoral Thesis, Dept. of Computer and Communication Sciences, University of Michigan, Ann Arbor, 1975.
K. DeJong and W. Spears, “A Formal Analysis of The Role of Multi-Point Crossover in Genetic Algorithms,” Annals of Math. AI Journal, Vol. 5, 1992, pp. 1–26.
D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley Pub. Company, 1989.
J. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, MI, 1975.
D. Johnson, C. Aragon, L. McGeoch, and C. Schevon, “Optimization by Simulated Annealing: An Experimental Evaluation, Part 1, Graph Partitioning,” Operations Research, 37, 1989, pp. 865–892.
C. Jones, Vertex and Edge Partitions of Graphs, Ph.D. Dissertation, Penn. State. Univ., University Park, 1992.
G. Syswerda, “Uniform Crossover in Genetic Algorithms,” Proc. of the 3rd Int. Conf. on Genetic Algorithms, June 1989, pp. 2–9.
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© 1994 Springer-Verlag Berlin Heidelberg
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Bui, T.N., Moon, BR. (1994). Analyzing hyperplane synthesis in genetic algorithms using clustered schemata. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_255
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DOI: https://doi.org/10.1007/3-540-58484-6_255
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