Results 221 to 230 of about 41,851 (257)

Genetic algorithm with modified reproduction strategy based on self-organizing map and usable schema

International Congress Series, 2006
Abstract In this paper, we propose a new updating method considering usability of each element of inputs and apply it to the reproduction of the GA to achieve more effective search than the traditional reproduction. In the proposed updating method, the order of updating elements is decided by averaging the corresponding elements multiplied by fitness
Ryosuke Kubota, Keiichi Horio, Takeshi Yamakawa   +2 more
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Exact Schema Theory and Markov Chain Models for Genetic Programming and Variable-length Genetic Algorithms with Homologous Crossover

Genetic Programming and Evolvable Machines, 2004
Genetic Programming (GP) homologous crossovers are a group of operators, including GP one-point crossover and GP uniform crossover, where the offspring are created preserving the position of the genetic material taken from the parents. In this paper we present an exact schema theory for GP and variable-length Genetic Algorithms (GAs) which is ...
Riccardo Poli, Nicholas Freitag McPhee, Jonathan E. Rowe   +2 more
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Evolving Mobile Prototypes towards the Best-Suited Design and Interaction Schema Using the Genetic Algorithm

International Journal of Mobile Human Computer Interaction, 2014
The recent advances in the mobile environment, such as multi-touch gestures paradigm, introduce new challenges for the interaction designers in producing the best-suited final prototype. Moreover, the short delivery-time pressure of the current mobile market makes it harder to perform the detailed evaluations for selecting the best prototype amongst ...
Ragaad AlTarawneh, Shah Rukh Humayoun
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Exact Schema Theory for Genetic Programming and Variable-Length Genetic Algorithms with One-Point Crossover

Genetic Programming and Evolvable Machines, 2001
Summary: A few schema theorems for genetic programming (GP) have been proposed in the literature in the last few years. Since they consider schema survival and disruption only, they can only provide a lower bound for the expected value of the number of instances of a given schema at the next generation rather than an exact value.
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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, ZHONG LI, JIN BAE PARK, YOUNG HOON JOO, XIANGYANG LI   +4 more
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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.
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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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A new insight into the schema survival after crossover and mutation for genetic algorithms having distributed population set

International Journal of Information Technology, 2018
Genetic algorithms are one of the most popular optimization algorithms. Schema theory provides a mathematical foundation for the working of genetic algorithm. Different variants of the basic genetic algorithm have been proposed; and genetic algorithm having distributed population set (Island model of genetic algorithm) is one of them.
Apoorva Mishra, Anupam Shukla
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A modified genetic algorithm based on the best schema and its application for function optimization

Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393), 2002
The genetic algorithm (GA) is a wildly employed evolutional algorithm in the field of combinatorial optimization. Criticism of this approach includes slow speed and premature result during the convergence procedure. Through introducing new crossover and mutation operators based on the best scheme, the paper proposes a more efficient method to improve ...
null Zi Gang, null Peng Chuwu, null Zou Mingzhu   +2 more
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A Heuristic Genetic Algorithm Based on Schema Replacement for 0-1 Knapsack Problem

2010 Fourth International Conference on Genetic and Evolutionary Computing, 2010
This paper investigates the 0-1 knapsack problem using genetic algorithms. The work is based on heuristic strategies that takes into account the characteristics of 0-1 knapsack problem. In this article, a heuristic Genetic Algorithms(GA) is proposed to solve the 0-1 knapsack problem, in each generation, populations are divided into two sections ...
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