Particle swarm optimization: an alternative in marine propeller optimization?
Journal article, 2018

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.


particle swarm optimization

cavitation constraints

marine propeller

Multi-objective optimization


Florian Vesting

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Rickard Bensow

Chalmers, Mechanics and Maritime Sciences (M2), Marine Technology

Engineering Optimization

0305-215X (ISSN) 1029-0273 (eISSN)

Vol. 4 83 1-19

Driving Forces

Sustainable development

Innovation and entrepreneurship

Areas of Advance



Subject Categories

Computational Mathematics

Vehicle Engineering


Basic sciences



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