Vivek T. Ramamoorthy
Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials
Ramamoorthy, Vivek T.; Özcan, Ender; Parkes, Andrew J.; Sreekumar, Abhilash; Jaouen, Luc; Bécot, François-Xavier
Authors
ENDER OZCAN ender.ozcan@nottingham.ac.uk
Professor of Computer Science and Operational Research
Dr ANDREW PARKES ANDREW.PARKES@NOTTINGHAM.AC.UK
Assistant Professor
Abhilash Sreekumar
Luc Jaouen
François-Xavier Bécot
Abstract
When designing sound packages, often fully filling the available space with acoustic materials is not the most absorbing solution. Better solutions can be obtained by creating cavities of air pockets, but determining the most optimal shape and topology that maximises sound absorption is a computationally challenging task. Many recent topology optimisation applications in acoustics use heuristic methods such as solid-isotropic-material-with-penalisation (SIMP) to quickly find near-optimal solutions. This study investigates seven heuristic and metaheuristic optimisation approaches including SIMP applied to topology optimisation of acoustic porous materials for absorption maximisation. The approaches tested are hill climbing, constructive heuristics, SIMP, genetic algorithm, tabu search, covariance-matrix-adaptation evolution strategy (CMA-ES), and differential evolution. All the algorithms are tested on seven benchmark problems varying in material properties, target frequencies, and dimensions. The empirical results show that hill climbing, constructive heuristics, and a discrete variant of CMA-ES outperform the other algorithms in terms of the average quality of solutions over the different problem instances. Though gradient-based SIMP algorithms converge to local optima in some problem instances, they are computationally more efficient. One of the general lessons is that different strategies explore different regions of the search space producing unique sets of solutions.
Journal Article Type | Article |
---|---|
Acceptance Date | Oct 3, 2021 |
Online Publication Date | Oct 27, 2021 |
Publication Date | Oct 1, 2021 |
Deposit Date | Oct 29, 2021 |
Publicly Available Date | Apr 2, 2022 |
Journal | The Journal of the Acoustical Society of America |
Print ISSN | 0001-4966 |
Electronic ISSN | 1520-8524 |
Publisher | Acoustical Society of America (ASA) |
Peer Reviewed | Peer Reviewed |
Volume | 150 |
Issue | 4 |
Pages | 3164-3175 |
DOI | https://doi.org/10.1121/10.0006784 |
Keywords | Acoustics and Ultrasonics; Arts and Humanities (miscellaneous) |
Public URL | https://nottingham-repository.worktribe.com/output/6544494 |
Publisher URL | https://asa.scitation.org/doi/pdf/10.1121/10.0006784 |
Additional Information | Copyright 2021 Acoustical Society of America. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the Acoustical Society of America. The following article appeared in The Journal of the Acoustical Society of America 150 (4), October 2021, and may be found at https://asa.scitation.org/doi/10.1121/10.0006784. |
Files
Comparison of heuristics and metaheuristics for topology optimisation in acoustic porous materials
(3.2 Mb)
PDF
You might also like
Acoustic topology optimisation using CMA-ES
(2020)
Conference Proceeding
Metaheuristic optimisation of sound absorption performance of multilayered porous materials
(2019)
Conference Proceeding
Learning the Quality of Dispatch Heuristics Generated by Automated Programming
(2018)
Book Chapter
Exploring the landscape of the space of heuristics for local search in SAT
(2017)
Conference Proceeding
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search