Search Results - (( adoption _ difference evolution algorithm ) OR ( adoption a difference evolutionary algorithm ))
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Published 2023“…Research works published from the year 2018 to 2022 are identified in terms of problem representation and evolutionary strategies adopted. The mechanisms and strategies used in evolutionary algorithms to address different types of combinatorial optimization problems are discovered. …”
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Evolutionary mating algorithm
Published 2023“…This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. …”
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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…Harmony Search (HS) algorithm has been extensively adopted in the literature to address optimization problems in many different fields, such as industrial design, civil engineering, electrical and mechanical engineering problems. …”
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An integrated reservoir modelling and evolutionary algorithm for optimizing field development in a mature fractured reservoir
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Optimal coordination of overcurrent relay protection using evolutionary programming / Noor Shah Rizal Abdul Manap
Published 2018“…Therefore, this research employed a metaheuristic optimization for Evolutionary Programming (EP) to find the optimum time for optimization overcurrent protection relay in radial distribution system. …”
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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…The Savitzky-Golay (SG) filter was adopted for smoothing and denoising the EEG dataset. …”
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A comparative study for parameter selection in online auctions
Published 2009“…In this work, three different models of genetic algorithms are considered. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Gradient-based mutation manta ray foraging optimization (gbm-mrfo) for solving constrained real-world problems
Published 2022“…MRFO is a recently new introduced algorithm that consists of strategy of foraging adopted by Manta Ray while Gradient-based Mutation (GbM) is a feasibility-and solution repair strategy adopted from ϵ-Matrix-Adaptation Evolution Strategy (ϵ-MAES). …”
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Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme
Published 2014“…The percentage difference is 2.1%,compared with the full feedback method, with only 0.5% degradation. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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Performance evaluation of intrusion detection system using selected features and machine learning classifiers
Published 2021“…These evolutionary-based algorithms are known to be effective in solving optimization problems. …”
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Computational methods for self-assembly of DNA nanostructures / Ong Hui San
Published 2016“…Several approaches have been adopted including development of an autonomous tool that incorporated evolutionary optimization algorithm in constructing these heterogeneous DNA shapes and the application of heuristic through undirected graph theory as an annotation schema to produce the connectivity maps. …”
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Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images
Published 2015“…So, a rank based feature selection algorithm is proposed to address these issues. …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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