Multi-objective topology optimisation for acoustic porous materials using gradient-based, gradient-free and hybrid strategies

Vivek T. Ramamoorthy, Ender Ozcan, Andrew J. Parkes, Luc Jaouen, Francois-Xavier Becot

Research output: Contribution to journalArticlepeer-review


When designing passive sound-attenuation structures, one of the challenging problems that arise is optimally distributing acoustic porous materials within a design region so as to maximise sound absorption while minimising material usage. To identify efficient optimisation strategies for this multi-objective problem, several gradient, non-gradient, and hybrid topology optimisation strategies are compared. For gradient approaches, the solid-isotropic-material-with-penalisation method and a gradient-based constructive heuristic are considered. For gradient-free approaches, hill climbing with a weighted-sum scalarisation and a non-dominated sorting genetic algorithm-II are considered. Optimisation trials are conducted on seven benchmark problems involving rectangular design domains in impedance tubes subject to normal-incidence sound loads. The results indicate that while gradient methods can provide quick convergence with high-quality solutions, often gradient-free strategies are able to find improvements in specific regions of the Pareto front. Two hybrid approaches are proposed, combining a gradient method for initiation and a non-gradient method for local improvements. An effective Pareto-slope-based weighted-sum hill climbing is introduced for local improvement. Results reveal that for a given computational budget, the hybrid methods can consistently outperform the parent gradient or non-gradient method.
Original languageEnglish
Pages (from-to)2945-2955
Number of pages11
JournalJournal of the Acoustical Society of America (JASA)
Issue number5
Publication statusPublished - 19 May 2023


  • Metaheuristics
  • Acoustics
  • Optimisation
  • Topology


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