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 …
Metaheuristic optimization algorithms: A comprehensive overview and classification of benchmark test functions
This review aims to exploit a study on different benchmark test functions used to evaluate the
performance of Meta-Heuristic (MH) optimization techniques. The performance of the MH …
performance of Meta-Heuristic (MH) optimization techniques. The performance of the MH …
An improved hybrid aquila optimizer and harris hawks algorithm for solving industrial engineering optimization problems
Aquila Optimizer (AO) and Harris Hawks Optimizer (HHO) are recently proposed meta-
heuristic optimization algorithms. AO possesses strong global exploration capability but …
heuristic optimization algorithms. AO possesses strong global exploration capability but …
An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …
deal with Feature Selection (FS) problems. FS is an important data reduction step in data …
Deep ensemble of slime mold algorithm and arithmetic optimization algorithm for global optimization
In this paper, a new hybrid algorithm based on two meta-heuristic algorithms is presented to
improve the optimization capability of original algorithms. This hybrid algorithm is realized by …
improve the optimization capability of original algorithms. This hybrid algorithm is realized by …
Towards develo** a machine learning-metaheuristic-enhanced energy-sensitive routing framework for the internet of things
The heterogeneous nature, communication constraints, multi-hop data transmissions, and
inherent challenges of wireless connections have caused routing and data transmission …
inherent challenges of wireless connections have caused routing and data transmission …
An Improved Teaching‐Learning‐Based Optimization Algorithm with Reinforcement Learning Strategy for Solving Optimization Problems
This paper presents an improved teaching‐learning‐based optimization (TLBO) algorithm
for solving optimization problems, called RLTLBO. First, a new learning mode considering …
for solving optimization problems, called RLTLBO. First, a new learning mode considering …
[PDF][PDF] An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems
Arithmetic optimization algorithm (AOA) is a newly proposed meta-heuristic method which is
inspired by the arithmetic operators in mathematics. However, the AOA has the weaknesses …
inspired by the arithmetic operators in mathematics. However, the AOA has the weaknesses …
A Hybrid SSA and SMA with Mutation Opposition‐Based Learning for Constrained Engineering Problems
Based on Salp Swarm Algorithm (SSA) and Slime Mould Algorithm (SMA), a novel hybrid
optimization algorithm, named Hybrid Slime Mould Salp Swarm Algorithm (HSMSSA), is …
optimization algorithm, named Hybrid Slime Mould Salp Swarm Algorithm (HSMSSA), is …
A Contemporary Systematic Review on Meta-heuristic Optimization Algorithms with Their MATLAB and Python Code Reference
Optimization is a method which is used in every field, such as engineering, space, finance,
fashion market, mass communication, travelling, and also in our daily activities. In every …
fashion market, mass communication, travelling, and also in our daily activities. In every …