An exhaustive review of the metaheuristic algorithms for search and optimization: taxonomy, applications, and open challenges
As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …
Cellulosic biomass fermentation for biofuel production: Review of artificial intelligence approaches
Scarcity in fossil fuel reserves and their environmental impacts has forced the world towards
the production of clean and environment-friendly fuels called biofuels. This review focuses …
the production of clean and environment-friendly fuels called biofuels. This review focuses …
[HTML][HTML] Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems
In this paper, a new metaheuristic algorithm called the Coati Optimization Algorithm (COA) is
introduced, which mimics coati behavior in nature. The fundamental idea of COA is the …
introduced, which mimics coati behavior in nature. The fundamental idea of COA is the …
Dandelion Optimizer: A nature-inspired metaheuristic algorithm for engineering applications
S Zhao, T Zhang, S Ma, M Chen - Engineering Applications of Artificial …, 2022 - Elsevier
This paper proposes a novel swarm intelligence bioinspired optimization algorithm, called
the Dandelion Optimizer (DO), for solving continuous optimization problems. DO simulates …
the Dandelion Optimizer (DO), for solving continuous optimization problems. DO simulates …
Liver Cancer Algorithm: A novel bio-inspired optimizer
This paper introduces a new bio-inspired optimization algorithm named the Liver Cancer
Algorithm (LCA), which mimics the liver tumor growth and takeover process. It uses an …
Algorithm (LCA), which mimics the liver tumor growth and takeover process. It uses an …
A new human-based metaheuristic algorithm for solving optimization problems on the base of simulation of driving training process
In this paper, a new stochastic optimization algorithm is introduced, called Driving Training-
Based Optimization (DTBO), which mimics the human activity of driving training. The …
Based Optimization (DTBO), which mimics the human activity of driving training. The …
Electric eel foraging optimization: A new bio-inspired optimizer for engineering applications
W Zhao, L Wang, Z Zhang, H Fan, J Zhang… - Expert Systems with …, 2024 - Elsevier
An original swarm-based, bio-inspired metaheuristic algorithm, named electric eel foraging
optimization (EEFO) is developed and tested in this work. EEFO draws inspiration from the …
optimization (EEFO) is developed and tested in this work. EEFO draws inspiration from the …
Improved binary grey wolf optimizer and its application for feature selection
Abstract Grey Wolf Optimizer (GWO) is a new swarm intelligence algorithm mimicking the
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …
A survey on swarm intelligence approaches to feature selection in data mining
One of the major problems in Big Data is a large number of features or dimensions, which
causes the issue of “the curse of dimensionality” when applying machine learning …
causes the issue of “the curse of dimensionality” when applying machine learning …
[HTML][HTML] SRL-ACO: A text augmentation framework based on semantic role labeling and ant colony optimization
A Onan - Journal of King Saud University-Computer and …, 2023 - Elsevier
The process of creating high-quality labeled data is crucial for training machine-learning
models, but it can be a time-consuming and labor-intensive process. Moreover, manual …
models, but it can be a time-consuming and labor-intensive process. Moreover, manual …