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Particle swarm optimization algorithm: review and applications
Published 2024“…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
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A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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Island flower pollination algorithm for global optimization
Published 2019“…Comparing the results of IsFPA with those of state-of-the-art methods which are FPA, genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), multi-verse optimizer (MVO), island bat algorithm (iBA), and island harmony search (iHS), the comparison results show that the IsFPA is able to control the diversity and improves the outcomes where IsFPA is ranked first followed by FPA, iBA, iHS, GSA, MVO, GA, PSO, respectively, based on the Friedman test with Holm and Hochberg as post hoc statistical test.…”
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An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications
Published 2021“…The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. …”
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Parameter Identification of Flexible Drive Systems using Particle Swarm Optimization
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Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System
Published 2024“…<p dir="ltr">The arbitrary selection of the Crow Search Algorithm (CSA) parameters, the Awareness Probability (AP) and the Flight Length (fl) results in poor convergence performance and efficiency even if the CSA performs well when solving global optimization problems. …”
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Optimizing MPPT Control for Enhanced Efficiency in Sustainable Photovoltaic Microgrids: A DSO-Based Approach
Published 2024“…Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. …”
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An intensive and comprehensive overview of JAYA algorithm, its versions and applications
Published 2021“…The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. …”
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Best Polynomial Harmony Search with Best β-Hill Climbing Algorithm
Published 2020“…Furthermore, the two proposed algorithms are compared against four versions of particle swarm optimization (PSO). …”
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Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms
Published 2023“…The performance of all 15 of the algorithms is likely to deteriorate due to certain transformations, while the 4 state-of-the-art metaheuristics are less affected by transformations such as the shifting of the global optimal point away from the center of the search space. …”
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Hybrid Bio-Inspired Routing Algorithms for Scalable and Adaptive Wireless Ad Hoc Networks
Published 2025“…In order to overcome such drawbacks, this paper has suggested a new hybrid bio-inspired routing protocol which combines the locally adaptive behav-ior characteristic of the Ant Colony Optimization (ACO) and the globally convergent efficiency of the Particle Swarm Optimization (PSO). …”
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An enhanced binary artificial rabbits optimization for feature selection in medical diagnosis
Published 2023“…ARO is a recent swarm-based optimization algorithm that mimics rabbits’ natural survival tactics and eating habits. …”
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A High‐Performance MPPT Solution for Solar DC Microgrids: Leveraging the Hippopotamus Algorithm for Greater Efficiency and Stability
Published 2025“…Performance of HA's is compared with three established optimization algorithms: Grey Wolf Optimization, Cuckoo Search Algorithm and Particle‐Swarm Optimization across different operating scenarios and partial shading circumstances. …”
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An Energy Efficient Wireless Sensor Network for Optimal Routing using Hybridized Bio-Inspired Technique
Published 2025“…While clustering techniques, such as Low Energy Adaptive Clustering Hierarchy (LEACH), help reduce energy usage, they suffer from inefficient local searches and poor exploration-exploitation balance.To address these limitations, this study proposes a hybrid bio-inspired optimization technique—Modified Harmony Search Algorithm (MHSA) combined with Competitive Swarm Optimization (CSO)—for optimal cluster head (CH) selection. …”
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Improving multilayer perceptron neural network using two enhanced moth-flame optimizers to forecast iron ore prices
Published 2024“…We compare our two proposed MFO algorithms, the roulette wheel moth-flame optimization algorithm and the global best moth-flame optimization algorithm, against four swarm intelligence algorithms and five classical machine learning techniques when predicting the iron ore price. …”
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