Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

All the population-based optimization algorithms are probabilistic algorithms and require
only a few control parameters including number of candidates, number of iterations, elite …

In this paper, we propose a new metaheuristic algorithm based on Lévy flight called Lévy
flight distribution (LFD) for solving real optimization problems. The LFD algorithm is inspired …

Despite the great efforts to find an effective way for coronavirus disease 2019 (COVID-19)
prediction, the virus nature and mutation represent a critical challenge to diagnose the …

Abstract Preparation of Convolutional Neural Networks (CNNs) for classification purposes
depends heavily on the knowledge of hyper-parameters tuning. This study aims, in particular …

Abstract Hierarchical Wireless Sensor Networks (WSNs) have got vital application domains
in modern era especially in monitoring and tracking of events, and without human …

A novel bio-inspired meta-heuristic algorithm, namely the American zebra optimization
algorithm (AZOA), which mimics the social behaviour of American zebras in the wild, is …

This study integrates a tunicate swarm algorithm (TSA) with a local esca** operator (LEO)
for overcoming the weaknesses of the original TSA. The LEO strategy in TSA-LEO prevents …

Whale optimization algorithm (WOA) is an emerging nature-inspired, swarmintelligence
based algorithm to solve optimization problems more efficiently. This algorithm is based on …

Optimization is the process of searching for the optimal (best-so-far) solution among a wide
range of solutions. Besides, in the last two decades, a family of algorithms known as …