ArticleArtificial intelligence review2023
An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges.
Article in Artificial intelligence review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 1 of them a synthesis that pooled it.
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Who cites it
58 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Stigmergy and Self-Organizing Systems in Swarm Robotics: A Systematic Review.Sensors (Basel, Switzerland) · 2026Pooled it
- Sunn Pest Optimization (SPO): A Phase-Differentiated Bio-Inspired Metaheuristic for Global Optimization with Application to Precision Agriculture Monitoring Networks.Biomimetics (Basel, Switzerland) · 2026Article
- Weather State Ants Optimizer: A Markov-Driven Variable-Structure Metaheuristic.Biomimetics (Basel, Switzerland) · 2026Article
- A Multi-Strategy Kangaroo Escape Optimization Technique for Global Optimization, Engineering Design, and Near-Infrared Prediction of Praeruptorin Content.Biomimetics (Basel, Switzerland) · 2026Article
- Experimental Characterization of Emergent Behavior in Bio-Inspired Swarm Intelligence Algorithms.Biomimetics (Basel, Switzerland) · 2026Article
- Enhanced Osprey Optimization Algorithm for Global Optimization with Application to PEM Fuel Cell Parameter Identification.Biomimetics (Basel, Switzerland) · 2026Article
- Chaotic Regulation of Exploration and Exploitation in Bio-Inspired Swarm Intelligence for Combinatorial Optimization.Biomimetics (Basel, Switzerland) · 2026Article
- AHGA-SA: A Novel Adaptive Hybrid Framework for Feature Selection in IoT-Oriented Intrusion Detection with Explainable AI.Sensors (Basel, Switzerland) · 2026Article
- HALA: A Hybrid Dual-Population Optimizer Integrating an Enhanced Artificial Lemming Algorithm and SHADE.Biomimetics (Basel, Switzerland) · 2026Article
- A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.Biomimetics (Basel, Switzerland) · 2026Review
- An in-depth analysis of UAV path planning, including procedures, algorithms, optimization models, and emerging challenges.MethodsX · 2026Review
- Hybrid Nature-Inspired Optimization for the Cell Formation Problem with Machine Reliability and Alternative Routings.Biomimetics (Basel, Switzerland) · 2026Article
- Metaheuristic optimization of deep CNNs for multi-class diagnosis of cervical cancer and lymphoma.Scientific reports · 2026Article
- Review
- DMARS_WGO: a deep reinforcement-driven hybrid metaheuristic for intelligent adaptive optimization.Scientific reports · 2026Article
- Explainable artificial intelligence-enabled intertwined logistics analytics with application in poultry vaccine distribution in the Northwest of Iran.Scientific reports · 2026Article
- Feature reduction using swarm optimization and random forest classifiers for early diabetes risk prediction.Scientific reports · 2026Article
- An Improved Artificial Bee Colony Algorithm with a Probabilistic Crossover and Lock Mechanism.Biomimetics (Basel, Switzerland) · 2026Article
- Adaptive multi mechanism integration in the crested porcupine optimizer for global optimization and engineering design problems.Scientific reports · 2026Article
- Learning-aided Artificial Bee Colony with neural knowledge transfer for global optimization.Scientific reports · 2026Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the world moves towards industrialization, optimization problems become more challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms (MAs) have been developed to date, with over 350 of them appearing in the last decade. The literature has grown significantly in recent years and should be thoroughly reviewed. In this study, approximately 540 MAs are tracked, and statistical information is also provided. Due to the proliferation of MAs in recent years, the issue of substantial similarities between algorithms with different names has become widespread. This raises an essential question: can an optimization technique be called 'novel' if its search properties are modified or almost equal to existing methods? Many recent MAs are said to be based on 'novel ideas', so they are discussed. Furthermore, this study categorizes MAs based on the number of control parameters, which is a new taxonomy in the field. MAs have been extensively employed in various fields as powerful optimization tools, and some of their real-world applications are demonstrated. A few limitations and open challenges have been identified, which may lead to a new direction for MAs in the future. Although researchers have reported many excellent results in several research papers, review articles, and monographs during the last decade, many unexplored places are still waiting to be discovered. This study will assist newcomers in understanding some of the major domains of metaheuristics and their real-world applications. We anticipate this resource will also be useful to our research community.
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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.