An intensive and comprehensive overview of JAYA algorithm, its versions and applications
In this review paper, JAYA algorithm, which is a recent population-based algorithm is
intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from …
intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from …
Optimization method for forecasting confirmed cases of COVID-19 in China
MAA Al-Qaness, AA Ewees, H Fan… - Journal of clinical …, 2020 - mdpi.com
In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China,
and has spread to different cities in China as well as to 24 other countries. The number of …
and has spread to different cities in China as well as to 24 other countries. The number of …
Differential evolution algorithm with wavelet basis function and optimal mutation strategy for complex optimization problem
W Deng, J Xu, Y Song, H Zhao - Applied Soft Computing, 2021 - Elsevier
The optimization performance of differential evolution (DE) algorithm significantly depends
on control parameters and mutation strategy. However, it is difficult to set suitable control …
on control parameters and mutation strategy. However, it is difficult to set suitable control …
Discrete spider monkey optimization for travelling salesman problem
Meta-heuristic algorithms inspired by biological species have become very popular in recent
years. Collective intelligence of various social insects such as ants, bees, wasps, termites …
years. Collective intelligence of various social insects such as ants, bees, wasps, termites …
Distributed Grey Wolf Optimizer for scheduling of workflow applications in cloud environments
BH Abed-Alguni, NA Alawad - Applied Soft Computing, 2021 - Elsevier
Optimal scheduling of workflows in cloud computing environments is an essential element to
maximize the utilization of Virtual Machines (VMs). In practice, scheduling of dependent …
maximize the utilization of Virtual Machines (VMs). In practice, scheduling of dependent …
Equilibrium optimizer: a comprehensive survey
Equilibrium optimizer (EO) is a recent optimization method inspired by the physical equation
of the mass balance that provides the conservation of mass entering, leaving, and …
of the mass balance that provides the conservation of mass entering, leaving, and …
Island-based Cuckoo Search with elite opposition-based learning and multiple mutation methods for solving optimization problems
BH Abed-alguni, D Paul - Soft Computing, 2022 - Springer
Abstract The island Cuckoo Search (i CSPM) algorithm is a variation of Cuckoo Search that
uses the island model and highly disruptive polynomial mutation to solve optimization …
uses the island model and highly disruptive polynomial mutation to solve optimization …
EEG signals denoising using optimal wavelet transform hybridized with efficient metaheuristic methods
Background. The most common and successful technique for signal denoising with
nonstationary signals, such as electroencephalogram (EEG) and electrocardiogram (ECG) …
nonstationary signals, such as electroencephalogram (EEG) and electrocardiogram (ECG) …
Discrete island-based cuckoo search with highly disruptive polynomial mutation and opposition-based learning strategy for scheduling of workflow applications in …
NA Alawad, BH Abed-alguni - Arabian Journal for Science and …, 2021 - Springer
The optimization-based scheduling algorithms used for scheduling workflows in cloud
computing environments may easily get trapped in local optima, especially in the beginning …
computing environments may easily get trapped in local optima, especially in the beginning …
An enhanced evolutionary software defect prediction method using island moth flame optimization
Software defect prediction (SDP) is crucial in the early stages of defect-free software
development before testing operations take place. Effective SDP can help test managers …
development before testing operations take place. Effective SDP can help test managers …