Results 111 to 120 of about 40,532 (179)
ON THE FITNESS OF HIGH ORDER SCHEMA OF A LINEAR-WEIGHTED CODED GENETIC ALGORITHM
Computational Intelligence in Decision and Control, 2008 According to Schema Theorem, the larger the fitness value of a schema is, the higher the chance of the sub-space corresponding to the schema being chosen for searching is. Therefore, the coding of a genetic algorithm should be designed to produces short building blocks at as more fixed positions of the strings as possible.
Hongqiang Mo +4 more
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Mathematical modeling analysis of genetic algorithms under schema theorem
Journal of Computational Methods in Sciences and Engineering, 2019 Genetic algorithm (GA) is a search algorithm for solving optimization problems and is an important part of evolutionary algorithms (EA). The main purpose of this research is to improve the mathematical modeling of GA, and to explore how to overcome the shortcomings of traditional algorithms under the Schema Theorem.
Donghai Liu
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The circular schema theorem for genetic algorithms and two-point crossover
Second International Conference on Genetic Algorithms in Engineering Systems, 1997 The schema theorem is the classical formulation of the search strategy performed by genetic algorithms (adaptation procedures mimicking biological evolution and molecular genetics). The original schema theorem has been derived for single-point crossover assuming that the individual chromosomes are arranged as strings.
André Neubauer
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Mapping XML Schema to Relations Using Genetic Algorithm
, 2004 As web-applications grow in number and complexity, there is a need for efficient mappings from XML schemas to the flat relational tables so that existing functions in relational database systems can be utilized. However, many of the existing mapping methods, such as the model-based or the structure-based methods, do not exploit query history for better
Vincent Ng, Chan Chi Kong, Stephen Chan
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Study on Genetic Algorithm Based on Schema Mutation and Its Performance Analysis
2009 Second International Symposium on Electronic Commerce and Security, 2009 Genetic algorithm (GA), as a kind of important intelligence computing tool, is a wide research content in the academic circle and the application domain now. In this paper, for the mutation operation of GA, by combining with the essential feature, we establish a genetic algorithm based on schema mutation (denoted by SM-GA, for short).
Fachao Li, Tingyu Zhang
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An exact schema theorem for adaptive genetic algorithm and its application to machine cell formation
Expert Systems with Applications, 2011 This paper proposes an exact schema theorem that is able to predict the expected number of copies of schemas in the next GA generation. It focuses on two-point crossover, which is widely used in many GA applications. As two important GA control parameters, crossover probability (p"c) and mutation probability (p"m) affect the performance of GAs ...
Xiao Feng Yin, Li Pheng Khoo
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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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Genetic algorithm based on schema comparison
Journal of Computer Applications, 2008 Yun Li
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Analysis of Schema Formation in Genetic Algorithms: A Review
Tiancong Zhang +4 more
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