Results 181 to 190 of about 12,025 (251)
Recursive Conditional Schema Theorem, Convergence and Population Sizing in Genetic Algorithms
, 2001 Abstract In this paper we start by presenting two forms of schema theorem in which expectations are not present. These theorems allow one to predict with a known probability whether the number of instances of a schema at the next generation will be above a given threshold.
Riccardo Poli
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Proceedings. International Conference on Power System Technology, 2003 A novel distribution network reconfiguration algorithm, named core schema genetic shortest-path algorithm (CSGSA) is proposed in this paper. It is based on the loads combination method. CSGSA consists of two steps: (1) searching for the optimal power supply paths for a sequence of loads one by one using shortest-path algorithm, and forming a core ...
Yixin Yu, Jianzhong Wu
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A reliability analysis of schema processing in genetic algorithms
TENCON'92 - Technology Enabling Tomorrow, 2003 An analysis of schema processing in simple genetic algorithms is presented. The hazard function (instantaneous failure rate) of a schema under fitness-proportionate selection, single-point crossover and mutation is computed, and the reliability expression is derived from the hazard function.
Uday K. Chakraborty +2 more
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GATuner: Tuning Schema Matching Systems Using Genetic Algorithms
2010 2nd International Workshop on Database Technology and Applications, 2010 Most recent schema matching systems combine multiple components, each of which employs a particular matching technique with several knobs. The multi-component nature has brought tuning problems for domain users. In this paper, we present GATuner, an approach to automatically tune schema matching systems using genetic algorithms. We match a given schema
Yuting Feng, Lei Zhao, Jiwen Yang
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Schema survival rates and heuristic search in genetic algorithms
[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence, 2002 Genetic algorithms are a relatively new paradigm for search in artificial intelligence. It is shown that, for certain kinds of search problems, called permutation problems, the ordinary rule for intermixing the genes between two organisms leads to longer search chains than are necessary. A schema is a partially completed organism.
Bill P. Buckles +2 more
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Schema analysis of multi-points crossover genetic algorithm
Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393), 2002 An extended schema theorem concerning two-point crossover and uniform crossover is deduced from one-point crossover schema theorem, and the conclusion that uniform crossover has advantage over two-point crossover and one-point crossover is made. The extended schema theorem provides theoretic foundation for the experimental results of Syswerda (1989).
Xu Hongze, Wei Xue Ye, Xu Maosheng
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Schema representation in virus-evolutionary genetic algorithm for knapsack problem
1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360), 2002 This paper deals with a genetic algorithm based on virus theory of evolution (VE-GA). VE-GA simulates coevolution of a host population of candidate solutions and a virus population of substring representing schemata. In the coevolutionary process, the virus individuals propagate partial genetic information in the host population by virus infection ...
Naoyuki Kubota, Toshio Fukuda
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SCHEMA ANALYSIS OF GENETIC ALGORITHMS ON MULTIPLICATIVE LANDSCAPE
, 2004 Hiroshi Furutani
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A simpler derivation of schema hazard in genetic algorithms
Information Processing Letters, 1995In a previous paper we derived an epression for the schema hazard function at any particular generation in the genetic algorithm. A much simpler derivation is presented here. It is more direct and eliminates the need for the use of the multinomial distribution and the multiple Poisson distribution.
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Analysis of Schema Formation in Genetic Algorithms: A Review
Tiancong Zhang +4 more
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