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Algorithm Selection on Adaptive Operator Selection: A Case Study on Genetic Algorithms
2021The present study applies Algorithm Selection (AS) to Adaptive Operator Selection (AOS) for further improving the performance of the AOS methods. AOS aims at delivering high performance in solving a given problem through combining the strengths of multiple operators.
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Genetic algorithms in feature and instance selection [PDF]
Knowledge-Based Systems, 2013 Feature selection and instance selection are two important data preprocessing steps in data mining, where the former is aimed at removing some irrelevant and/or redundant features from a given dataset and the latter at discarding the faulty data. Genetic algorithms have been widely used for these tasks in related studies.
Chih-Fong Tsai +2 more
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Entropy-Boltzmann selection in the genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 2003A new selection method, entropy-Boltzmann selection, for genetic algorithms (GAs) is proposed. This selection method is based on entropy and importance sampling methods in Monte Carlo simulation. It naturally leads to adaptive fitness in which the fitness function does not stay fixed but varies with the environment.
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Sensor Selection Optimization with Genetic Algorithms
2019 IEEE SENSORS, 2019Sensor networks and systems may incorporate sensors and sensor platforms of various quality and security. Current methods of sensor selection fail to produce effective and efficient decisions and to scale up to real-life cases. This paper develops and describes an intelligent optimization technique based on the genetic algorithms, whose execution time ...
Leon Reznik +2 more
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Genetic Algorithm With Species And Sexual Selection
2006 IEEE Conference on Cybernetics and Intelligent Systems, 2006In this paper we have proposed new real coded genetic algorithm with species and sexual selection (GAS3). GAS3 is a distributed quasi steady-state real-coded genetic algorithm. GAS3 uses sex determination method (SDM) to determine the sex (male or female) of members in population.
O. G. Kakde, Mukesh M. Raghuwanshi
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A thermodynamical selection rule for the genetic algorithm
Proceedings of 1995 IEEE International Conference on Evolutionary Computation, 2002The genetic algorithrri (GX), an optiriiizatioii tcchriiqiic bascd OII tlie proccss of cl-olutioii, suffers from a phenorrienon called prcrriature coiiwrgciicc. Tlia: is. the spstciri oftcii loses diversity of the population at ail earl?- stage of scarchirig. Iri this paper.
J. Yoshida +3 more
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Probabilistic selection in cellular genetic algorithm
2012 8th International Conference on Natural Computation, 2012In this paper, we introduce a new selection operator, namely, a Probabilistic Selection operator which allows us to control the selection pressure in cellular genetic algorithms through reducing the effective neighborhood radius. One advantage for having probabilistic selection is that, once we have our probability density function in hand, we can ...
Teong-Joo Ong +2 more
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Selection Analysis in Genetic Algorithms
1998This paper describes a formal framework for the analysis of genetic algorithms. The model is based on the idea that over the space of populations an equivalence relation can be defined, as well as a metric on the space of equivalence classes induced by this relation.
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A Genetic Algorithm for the Index Selection Problem
2003This paper considers the problem of minimizing the response time for a given database workload by a proper choice of indexes. This problem is NP-hard and known in the literature as the Index Selection Problem (ISP). We propose a genetic algorithm (GA) for solving the ISP.
Dušan Tošić +2 more
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Genetic programming as a feature selection algorithm
2014 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC), 2014Genetic Programming (GP) is an Evolutionary Algorithm commonly used to evolve computer programs in order to solve a particular task. Therefore, GP has been used to tackle different problems like classification and regression. In this work, the capabilities of GP in other types of problems are explored, particularly the feature selection problem.
Jose Maria Valencia-Ramirez +2 more
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