Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …

In next-generation networks (NGN), a very large number of devices and applications are
emerged, along with the heterogeneity of technologies, architectures, mobile data, etc., and …

In recent decades, researches on optimizing the parameter of the artificial neural network
(ANN) model has attracted significant attention from researchers. Hybridization of superior …

Maritime inventory routing problem is addressed in this paper to satisfy the demand at
different ports during the planning horizon. It explores the possibilities of integrating slow …

Aiming at the problems of poor diversity and slow convergence of ant colony algorithm,
dynamic multi-role adaptive collaborative ant colony optimization (MRCACO) is proposed in …

Particle swarm optimization (PSO) is considered one of the most important methods in
swarm intelligence. PSO is related to the study of swarms; where it is a simulation of bird …

In quantitative structure–activity relationship (QSAR) classification, descriptor selection is
one of the most important topics in the chemometrics. The selection of descriptors can be …

Recently, virtual coupling has aroused increasing interest in regard to achieving flexible and
on-demand train operations. However, one of the main challenges in increasing the …

With rapid development of the healthcare network, the location-allocation problems of public
facilities under increased integration and aggregation needs have been widely researched …

Nowadays expert systems have been used in different fields. They must be able to operate
as quickly and efficiently as possible. So, they need optimization mechanism in their different …