Results 11 to 20 of about 190,584 (312)
Neural Computing and Applications, 2022 This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. The algorithm is based on the adoption of random mating concept from Hardy–Weinberg equilibrium and crossover index in order to produce new offspring. In this algorithm, effect of the environmental factor (i.e.
Mohd Herwan Sulaiman +4 more
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An island based hybrid evolutionary algorithm for optimization [PDF]
, 2008 This is a post-print version of the article - Copyright @ 2008 Springer-VerlagEvolutionary computation has become an important problem solving methodology among the set of search and optimization techniques. Recently, more and more different evolutionary
Yang, S +5 more
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Hetero-Dimensional Multitask Neuroevolution for Chaotic Time Series Prediction
IEEE Access, 2020 Chaotic time series prediction has important research and application value, and neural network-based prediction methods have problems such as low accuracy and difficulty in determining the number of nodes in the hidden layer.
Daoqing Zhang, Mingyan Jiang
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, 2018 Evolutionary algorithms (EAs) are population-based metaheuristics, originally inspired by aspects of natural evolution. Modern varieties incorporate a broad mixture of search mechanisms, and tend to blend inspiration from nature with pragmatic engineering concerns; however, all EAs essentially operate by maintaining a population of potential solutions ...
David W. Corne, Michael A. Lones
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Evolutionary algorithm design based on evolutionary efficiency factor
Journal of Hebei University of Science and Technology, 2018 With the development of electronic chip technology, circuit systems become gradually high integrated and intelligent. Under the interface of complex electromagnetic field environment, the requirements for the stability and reliability of information ...
Huicong WU, Jie YU
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Hybrid Multi-Evolutionary Algorithm to Solve Optimization Problems
Applied Artificial Intelligence, 2020 The article presents a Hybrid Multi-Evolutionary Algorithm designed to solve optimization problems. The Genetic Algorithm and Evolutionary Strategy work together to improve the efficiency of optimization and increase resistance to getting stuck to sub ...
Krzysztof Pytel
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A Fireworks Algorithm Based on Transfer Spark for Evolutionary Multitasking
Frontiers in Neurorobotics, 2020 In recent years, lots of multifactorial optimization evolutionary algorithms have been developed to optimize multiple tasks simultaneously, which improves the overall efficiency using implicit genetic complementarity between different tasks.
Zhiwei Xu +6 more
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A Multiclustering Evolutionary Hyperrectangle-Based Algorithm
International Journal of Computational Intelligence Systems, 2023 Clustering is a grouping technique that has long been used to relate data homogeneously. With the huge growth of complex datasets from different sources in the last decade, new paradigms have emerged.
Luis Alfonso Pérez Martos +3 more
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Hybrid evolutionary optimization algorithm MPSO-SA [PDF]
International Journal for Simulation and Multidisciplinary Design Optimization, 2010 This paper proposes a new method for a modified particle swarm optimization algorithm (MPSO) combined with a simulated annealing algorithm (SA). MPSO is known as an efficient approach with a high performance of solving optimization problems in many ...
El Hami N., Ellaia R., Itmi M.
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Applications of Modelling and Simulation, 2023 The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. The adaptability of evolutionary algorithm mechanisms provides diverse approaches to handle combinatorial optimization challenges.
Anniza Hamdan +4 more
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