Comparative Study of Particle Swarm Optimization and Genetic Algorithm for the Migration from an Existing Network to a New Generation Network

Authors : Raphaël NLEND, Emmanuel TONYE

Volume/Issue : Volume 4 - 2019, Issue 7 - July

Google Scholar :

Scribd :

In this paper we model the problem of base station migration as an optimization issue by the use of particle swarm algorithm in order to minimize a target goal which is a weighted function of network coverage, traffic, energy consumption and the cost of infrastructure. We then compare the results with those obtained by applying the genetic algorithm under the same conditions. Overall, genetic algorithms are more efficient than particle swarms for the network migration problem.

Keywords : Cellular network planning, Genetic Algorithm, Particle swarm optimisation.


Paper Submission Last Date
31 - October - 2023

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.