ReviewPloS one2015
A comprehensive review of swarm optimization algorithms.
Review in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed.
- An adaptive oppositional grey wolf optimizer for complex engineering problems.Scientific reports · 2026Article
- Deep learning for apple leaf disease diagnosis: a comparative study with convolutional neural networks and transformers.Scientific reports · 2026Article
- Multi scenario chaotic transient search optimization algorithm for global optimization technique.Scientific reports · 2025Article
- A hybrid Harris Hawks Optimization with Support Vector Regression for air quality forecasting.Scientific reports · 2025Article
- Harmonic oscillator based particle swarm optimization.PloS one · 2025Article
- Predicting IVF outcomes using a logistic regression-ABC hybrid model: A proof-of-concept study on supplement associations.PloS one · 2025Article
- Article
- Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders.PloS one · 2025Article
- Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification.Scientific reports · 2024Article
- Temporal meta-optimiser based sensitivity analysis (TMSA) for agent-based models and applications in children's services.Scientific reports · 2024Article
- Agent-based modeling of the prostate tumor microenvironment uncovers spatial tumor growth constraints and immunomodulatory properties.NPJ systems biology and applications · 2024Article
- Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection.TheScientificWorldJournal · 2024Article
- An Interpretable Digital Twin for Self-Aware Industrial Machines.Sensors (Basel, Switzerland) · 2023Article
- Article
- Appropriate noise addition to metaheuristic algorithms can enhance their performance.Scientific reports · 2023Article
- Fuzzy-based hunger games search algorithm for global optimization and feature selection using medical data.Neural computing & applications · 2023Article
- Estimation of electrical transformer parameters with reference to saturation behavior using artificial hummingbird optimizer.Scientific reports · 2022Article
- An Intelligent Motor Imagery Detection System Using Electroencephalography with Adaptive Wavelets.Sensors (Basel, Switzerland) · 2022Article
- Modeling of Respiratory Motion to Support the Minimally Invasive Destruction of Liver Tumors.Sensors (Basel, Switzerland) · 2022Article
- The fusion-fission optimization (FuFiO) algorithm.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many swarm optimization algorithms have been introduced since the early 60's, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.