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Selecting Simulation Algorithm Portfolios by Genetic Algorithms
2010 IEEE Workshop on Principles of Advanced and Distributed Simulation, 2010An algorithm portfolio is a set of algorithms that are bundled together for increased overall performance. While being mostly applied to computationally hard problems so far, we investigate portfolio selection for simulation algorithms and focus on their application to adaptive simulation replication.
Roland Ewald +2 more
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Genetic Operators Impact on Genetic Algorithms Based Variable Selection
2020This paper faces the problem of variables selection through the use of a genetic algorithm based metaheuristic approach. The method is based on the evolution of a population of variables subsets, which is led by the genetic operators determining their selection and improvement through the algorithm generations. The impact of different genetic operators
Vannucci M., Colla V., Cateni S.
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Information Sciences, 2020
A multi-objective feature selection approach for selecting key quality characteristics (KQCs) of unbalanced production data is proposed. We define KQC (feature) selection as a bi-objective problem of maximizing the quality characteristic (QC) subset ...
An-Da Li, Bing Xue, Mengjie Zhang
semanticscholar +1 more source
A multi-objective feature selection approach for selecting key quality characteristics (KQCs) of unbalanced production data is proposed. We define KQC (feature) selection as a bi-objective problem of maximizing the quality characteristic (QC) subset ...
An-Da Li, Bing Xue, Mengjie Zhang
semanticscholar +1 more source
Feature Selection using Genetic Algorithm
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion, 2016Genetic algorithms (GAs) have been used for feature selection with binary representation. Even if binary representation has perfect probability to include or remove a feature in the search process, some works in the field of chemometrics have reported criticism about a high number of features selected by GA implementations.
Lauro C.M. de Paula +3 more
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A Nested Genetic Algorithm for feature selection in high-dimensional cancer Microarray datasets
Expert systems with applications, 2019Cancer is a dangerous disease that causes death worldwide. Discovering few genes relevant to one cancer disease can result in effective treatments. The challenge associated with the Microarray datasets is its high dimensionality; the huge number of ...
Sabah Sayed +3 more
semanticscholar +1 more source
Applied Soft Computing, 2019
The constraints on the battery resources of sensor nodes have been the major stumbling block in achieving the network longevity and in exploring the potential of Wireless Sensor Network (WSN) to the maximum level.
Sandeep Verma, Neetu Sood, A. Sharma
semanticscholar +1 more source
The constraints on the battery resources of sensor nodes have been the major stumbling block in achieving the network longevity and in exploring the potential of Wireless Sensor Network (WSN) to the maximum level.
Sandeep Verma, Neetu Sood, A. Sharma
semanticscholar +1 more source
Sexual Selection for Genetic Algorithms
Artificial Intelligence Review, 2003Genetic Algorithms (GA) have been widely used in operations research and optimization since first proposed. A typical GA comprises three stages, the encoding, the selection and the recombination stages. In this work, we focus our attention on the selection stage of GA, and review a few commonly employed selection schemes and their associated scaling ...
GOH, Kai Song +2 more
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Component Selection Using Genetic Algorithms
19th Design Automation Conference: Volume 1 — Mechanical System Dynamics; Concurrent and Robust Design; Design for Assembly and Manufacture; Genetic Algorithms in Design and Structural Optimization, 1993Abstract Genetic algorithms are investigated for use in obtaining optimal component configurations in dynamic engineering systems. Given a system layout, a database of component information from manufacturers’ catalogs, and a design specification, genetic algorithms are used to successfully select an optimal set of components.
Susan E. Carlson +2 more
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Mathematics and Computers in Simulation, 2019
Nowadays, with the development of information technology and economic globalization, supplier selection problem gets more and more attraction. The recent literature shows huge interest in hybrid artificial intelligence (AI)-based models for solving ...
Jing Luan, Z. Yao, Fu Tao Zhao, Xin Song
semanticscholar +1 more source
Nowadays, with the development of information technology and economic globalization, supplier selection problem gets more and more attraction. The recent literature shows huge interest in hybrid artificial intelligence (AI)-based models for solving ...
Jing Luan, Z. Yao, Fu Tao Zhao, Xin Song
semanticscholar +1 more source
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021
This paper proposes an innovative selection operator based on concepts from quantum mechanics. In particular, a quantum state is used to embody genetic individuals and their fitness values, and a quantum algorithm known as amplitude amplification is used to modify this state in order to create a quantum superposition in which the probability to measure
Acampora G. +2 more
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This paper proposes an innovative selection operator based on concepts from quantum mechanics. In particular, a quantum state is used to embody genetic individuals and their fitness values, and a quantum algorithm known as amplitude amplification is used to modify this state in order to create a quantum superposition in which the probability to measure
Acampora G. +2 more
openaire +2 more sources