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 …
[HTML][HTML] A review of metaheuristic algorithms for solving TSP-based scheduling optimization problems
Activity-based scheduling optimization is a combinatorial problem built on the traveling
salesman problem intending to optimize people schedules considering their trips and the …
salesman problem intending to optimize people schedules considering their trips and the …
Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis
W Shan, Z Qiao, AA Heidari, H Chen… - Knowledge-Based …, 2021 - Elsevier
Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …
marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode …
B-MFO: a binary moth-flame optimization for feature selection from medical datasets
Advancements in medical technology have created numerous large datasets including
many features. Usually, all captured features are not necessary, and there are redundant …
many features. Usually, all captured features are not necessary, and there are redundant …
An intensify Harris Hawks optimizer for numerical and engineering optimization problems
Abstract Recently developed Harris Hawks Optimization has virtuous behavior for finding
optimum solution in search space. However, it easily get trapped into local search space for …
optimum solution in search space. However, it easily get trapped into local search space for …
Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations
In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …
order to efficiently address complex optimization problems. In the last years the number of …
Forecasting stock price using integrated artificial neural network and metaheuristic algorithms compared to time series models
M Shahvaroughi Farahani, SH Razavi Hajiagha - Soft computing, 2021 - Springer
Today, stock market has important function and it can be a place as a measure of economic
position. People can earn a lot of money and return by investing their money in the stock …
position. People can earn a lot of money and return by investing their money in the stock …
Review of economic dispatch in multi-area power system: State-of-the-art and future prospective
Efficient and cost-effective coordination of online generation facilities is essential to the
reliable operation multi-area power system (PS) especially in a deregulated environment …
reliable operation multi-area power system (PS) especially in a deregulated environment …
Binary sand cat swarm optimization algorithm for wrapper feature selection on biological data
A Seyyedabbasi - Biomimetics, 2023 - mdpi.com
In large datasets, irrelevant, redundant, and noisy attributes are often present. These
attributes can have a negative impact on the classification model accuracy. Therefore …
attributes can have a negative impact on the classification model accuracy. Therefore …
New binary whale optimization algorithm for discrete optimization problems
The whale optimization algorithm (WOA) is an intelligence-based technique that simulates
the hunting behaviour of humpback whales in nature. In this article, an adaptation of the …
the hunting behaviour of humpback whales in nature. In this article, an adaptation of the …