relation: https://khub.utp.edu.my/scholars/16167/
title: Chaotic Simulator for Bilevel Optimization of Virtual Machine Placements in Cloud Computing
creator: Ganesan, T.
creator: Vasant, P.
creator: Litvinchev, I.
description: The drastic increase in engineering system complexity has spurred the development of highly efficient optimization techniques. Many real-world optimization problems have been identified as bilevel/multilevel as well as multiobjective. The primary aim of this work is to present a framework to tackle the bilevel virtual machine (VM) placement problem in cloud systems. This is done using the coupled map lattice (CML) approach in conjunction with the Stackelberg game theory and weighted-sum frameworks. The VM placement problem was modified from the original multiobjective (MO) problem to an MO bilevel formulation to make it more realistic albeit more complicated. Additionally comparative analysis on the performance of the CML approach was carried out against the particle swarm optimization method. A new bilevel metric called the cascaded hypervolume indicator is introduced and applied to measure the dominance of the solutions produced by both methods. Detailed analysis on the computational results is presented. © 2021, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany, part of Springer Nature.
publisher: Springer
date: 2022
type: Article
type: PeerReviewed
identifier:   Ganesan, T. and Vasant, P. and Litvinchev, I.  (2022) Chaotic Simulator for Bilevel Optimization of Virtual Machine Placements in Cloud Computing.  Journal of the Operations Research Society of China, 10 (4).  pp. 703-723.  ISSN 2194668X     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85100778457&doi=10.1007%2fs40305-020-00326-5&partnerID=40&md5=2afee8b1aba1f605012bfa9228243f11
relation: 10.1007/s40305-020-00326-5
identifier: 10.1007/s40305-020-00326-5