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The GA-P: a genetic algorithm and genetic programming hybrid

IEEE Expert, 1995
The GA-P performs symbolic regression by combining the traditional genetic algorithms function optimization strength with the genetic-programming paradigm to evolve complex mathematical expressions capable of handling numeric and symbolic data. This technique should provide new insights into poorly understood data relationships. >
Les M. Howard, Donna J. D'Angelo
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GA-Ensemble: a genetic algorithm for robust ensembles

Computational Statistics, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dong-Yop Oh, J. Brian Gray
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A genetic algorithm for the 1D electron gas

Physica A: Statistical Mechanics and its Applications, 2008
Abstract We show how to apply a genetic algorithm to describe the homogeneous electron gas. For simplicity we consider just the 1D case. The pair correlation function so obtained is compared with those found by using variational Monte Carlo and quantum hypernetted chain calculations and reported for the first time in this paper.
César O. Stoico   +2 more
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Application of Genetic Algorithms (GA) for the Optimization of Riveted Joints

Materials Testing, 2013
Abstract Genetic algorithms have an effective search technique in a predefined research space based on natural selection theory. They use the same combination of selection, recombination, and mutation to evolve a solution to a problem.
Baskal, Tamer   +3 more
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Genetic Algorithms (GAs) and Their Mathematical Foundations

2021
In this chapter, the authors back GA procedures using old mathematical facts. More rigorous working of mathematical facts about GAs are raised in this chapter. In fact, there are a large number of similarities in the population of strings. The authors see how GA exploits these similarities to generate good solutions.
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Forking Genetic Algorithms: GAs with Search Space Division Schemes

Evolutionary Computation, 1997
In this article, we propose a new type of genetic algorithm (GA), the forking GA (fGA), which divides the whole search space into subspaces, depending on the convergence status of the population and the solutions obtained so far. The fGA is intended to deal with multimodal problems that are difficult to solve using conventional GAs.
Shigeyoshi Tsutsui   +2 more
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QCs scheduling scheme of genetic algorithm (GA) and improved firefly algorithm (FA)

Cluster Computing, 2018
As an important part of container logistics, quay cranes (QCs) are crucial equipment in multimodal container transportation. The scheduling and allocation of QCs determine the operational efficiency of container terminals. By analyzing the way quay cranes are operated, this paper establishes a mixed-integer dynamic rolling-horizon programming model for
Liangcai Dong, Yang Yang 0058, Siyun Sun
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Genetic algorithms (GAs) to evolve multiple-agent cooperative systems

Artificial Life and Robotics, 1999
In this paper, a microrobot soccer-playing game, such as that of MIROSOT (Microrobot World Cup Soccer Tournament), is adopted as a standard test bed for research on multiple-agent cooperative systems. It is considerably complex and requires expertise in several difficult research topics, such as mobile microrobot design, motor control, sensor ...
Masanori Sugisaka   +2 more
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