Hybrid approaches to optimization and machine learning methods: a systematic literature review

BF Azevedo, AMAC Rocha, AI Pereira - Machine Learning, 2024‏ - Springer
Notably, real problems are increasingly complex and require sophisticated models and
algorithms capable of quickly dealing with large data sets and finding optimal solutions …

Machine and deep learning for resource allocation in multi-access edge computing: A survey

H Djigal, J Xu, L Liu, Y Zhang - IEEE Communications Surveys …, 2022‏ - ieeexplore.ieee.org
With the rapid development of Internet-of-Things (IoT) devices and mobile communication
technologies, Multi-access Edge Computing (MEC) has emerged as a promising paradigm …

Greylag goose optimization: nature-inspired optimization algorithm

ESM El-Kenawy, N Khodadadi, S Mirjalili… - Expert Systems with …, 2024‏ - Elsevier
Nature-inspired metaheuristic approaches draw their core idea from biological evolution in
order to create new and powerful competing algorithms. Such algorithms can be divided into …

[HTML][HTML] Optimization, validation and analyses of a hybrid PV-battery-diesel power system using enhanced electromagnetic field optimization algorithm and ε …

C Zhu, Y Zhang, M Wang, J Deng, Y Cai, W Wei, M Guo - Energy Reports, 2024‏ - Elsevier
This study introduces and assesses a hybrid renewable energy system tailored for a
practical, off-grid location. The integrated power system comprises a diesel generator …

Parameter adaptation-based ant colony optimization with dynamic hybrid mechanism

X Zhou, H Ma, J Gu, H Chen, W Deng - Engineering Applications of …, 2022‏ - Elsevier
In this paper, a parameter adaptation-based ant colony optimization (ACO) algorithm based
on particle swarm optimization (PSO) algorithm with the global optimization ability, fuzzy …

Multi-strategy particle swarm and ant colony hybrid optimization for airport taxiway planning problem

W Deng, L Zhang, X Zhou, Y Zhou, Y Sun, W Zhu… - Information …, 2022‏ - Elsevier
As the connecting hub of the airport runways and gates, the taxiway plays a very important
role in the rational allocation and utilization of the airport resources. In this paper, a multi …

An improved quantum-inspired differential evolution algorithm for deep belief network

W Deng, H Liu, J Xu, H Zhao… - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
Deep belief network (DBN) is one of the most representative deep learning models.
However, it has a disadvantage that the network structure and parameters are basically …

A novel gate resource allocation method using improved PSO-based QEA

W Deng, J Xu, H Zhao, Y Song - IEEE Transactions on …, 2020‏ - ieeexplore.ieee.org
With the continuous and rapid growth of air traffic demand, gate resource becomes a major
bottleneck restricting airport development. Rational gate allocation is regarded as one of the …

Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy

D Zhao, L Liu, F Yu, AA Heidari, M Wang… - Knowledge-Based …, 2021‏ - Elsevier
Although the continuous version of ant colony optimizer (ACOR) has been successfully
applied to various problems, there is room to boost its stability and improve convergence …

Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies

H Chen, AA Heidari, H Chen, M Wang, Z Pan… - Future Generation …, 2020‏ - Elsevier
The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …