ArticleArchives of computational methods in engineering : state of the art reviews2023
Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications.
Article in Archives of computational methods in engineering : state of the art reviews, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- SMA-WSN: Failure-Aware Slime-Mold-Inspired Clustering and Per-Hop Versus End-to-End Delivery Analysis in Agricultural Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2026Article
- Secant Optimization Algorithm for efficient global optimization.Scientific reports · 2026Article
- Energy efficient clustering protocol in wireless sensor networks using an adaptive hybrid optimization algorithm.Scientific reports · 2026Article
- Improving women football tactics analysis by using extreme learning and accumulated optimization algorithm.Scientific reports · 2025Article
- An optimized deep learning based hybrid model for prediction of daily average global solar irradiance using CNN SLSTM architecture.Scientific reports · 2025Article
- Sturnus vulgaris escape algorithm and its application to mechanical design.Scientific reports · 2025Article
- A quasi-opposition learning and chaos local search based on walrus optimization for global optimization problems.Scientific reports · 2025Article
- Novel empress SARANI optimization algorithm for active power loss reduction and voltage stability enhancement.Heliyon · 2024Article
- Kombucha-Proteinoid Crystal Bioelectric Circuits.ACS omega · 2024Article
- Improved genetic algorithm for multi-threshold optimization in digital pathology image segmentation.Scientific reports · 2024Article
- Multi-objective liver cancer algorithm: A novel algorithm for solving engineering design problems.Heliyon · 2024Article
- Research on Microgrid Optimal Dispatching Based on a Multi-Strategy Optimization of Slime Mould Algorithm.Biomimetics (Basel, Switzerland) · 2024Article
- Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules.Scientific reports · 2024Article
- Marine Predator Algorithm-Based Optimal PI Controllers for LVRT Capability Enhancement of Grid-Connected PV Systems.Biomimetics (Basel, Switzerland) · 2024Article
- Feature selection algorithm based on optimized genetic algorithm and the application in high-dimensional data processing.PloS one · 2024Article
- Latest advancements and prospects in the next-generation of Internet of Things technologies.PeerJ. Computer science · 2024Article
- Bone metastasis detection method based on improving golden jackal optimization using whale optimization algorithm.Scientific reports · 2023Article
- Article
- A new bio-inspired metaheuristic algorithm for solving optimization problems based on walruses behavior.Scientific reports · 2023Article
- American zebra optimization algorithm for global optimization problems.Scientific reports · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Meta-heuristic algorithms have a high position among academic researchers in various fields, such as science and engineering, in solving optimization problems. These algorithms can provide the most optimal solutions for optimization problems. This paper investigates a new meta-heuristic algorithm called Slime Mould algorithm (SMA) from different optimization aspects. The SMA algorithm was invented due to the fluctuating behavior of slime mold in nature. It has several new features with a unique mathematical model that uses adaptive weights to simulate the biological wave. It provides an optimal pathway for connecting food with high exploration and exploitation ability. As of 2020, many types of research based on SMA have been published in various scientific databases, including IEEE, Elsevier, Springer, Wiley, Tandfonline, MDPI, etc. In this paper, based on SMA, four areas of hybridization, progress, changes, and optimization are covered. The rate of using SMA in the mentioned areas is 15, 36, 7, and 42%, respectively. According to the findings, it can be claimed that SMA has been repeatedly used in solving optimization problems. As a result, it is anticipated that this paper will be beneficial for engineers, professionals, and academic scientists.
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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.