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Particle swarm optimization: an alternative in marine propeller optimization?

Florian Vesting (Institutionen för sjöfart och marin teknik, Marin teknik) ; Rickard Bensow ( Institutionen för mekanik och maritima vetenskaper, Marin teknik)
Engineering Optimization (0305-215X). Vol. 4 (2017), 83, p. 1-19.
[Artikel, refereegranskad vetenskaplig]

This article deals with improving and evaluating the performance of two evolutionary algorithm approaches for automated engineering design optimization. Here a marine propeller design with constraints on cavitation nuisance is the intended application. For this purpose, the particle swarm optimization (PSO) algorithm is adapted for multi-objective optimization and constraint handling for use in propeller design. Three PSO algorithms are developed and tested for the optimization of four commercial propeller designs for different ship types. The results are evaluated by interrogating the generation medians and the Pareto front development. The same propellers are also optimized utilizing the well established NSGA-II genetic algorithm to provide benchmark results. The authors' PSO algorithms deliver comparable results to NSGA-II, but converge earlier and enhance the solution in terms of constraints violation.

Nyckelord: cavitation constraints , marine propeller , Multi-objective optimization , NSGA-II , particle swarm optimization



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Denna post skapades 2017-08-14.
CPL Pubid: 251087

 

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Institutioner (Chalmers)

Institutionen för sjöfart och marin teknik, Marin teknik (2015-2017)
Institutionen för mekanik och maritima vetenskaper, Marin teknik

Ämnesområden

Energi
Transport
Hållbar utveckling
Innovation och entreprenörskap (nyttiggörande)
Optimeringslära, systemteori
Farkostteknik

Chalmers infrastruktur