Multi-objective optimisation of marine propellers

Seyedali Mirjalili, Andrew Lewis, Seyed Ali Mohammad Mirjalili

Research output: Contribution to journalConference articlepeer-review

32 Citations (Scopus)


Real world problems have usually multiple objectives. These objective functions are often in conflict, making them highly challenging in terms of determining optimal solutions and analysing solutions obtained. In this work Multi-objective Particle Swarm Optimisation (MOPSO) is employed to optimise the shape of marine propellers for the first time. The two objectives identified are maximising efficiency and minimising cavitation. Several experiments are undertaken to observe and analyse the impacts of structural parameters (shape and number of blades) and operating conditions (RPM) on both objective. The paper also investigates the negative effects of uncertainties in parameters and operating conditions on efficiency and cavitation. Firstly, the results showed that MOPSO is able to find a very accurate and uniformly distributed approximation of the true Pareto optimal front. The analysis of the results also shows that a propeller with 5 or 6 blades operating between 180 and 190 RPM results in the best trade-offs for efficiency and cavitation. Secondly, the simulation results show the significant negative impacts of uncertainties on both objectives.

Original languageEnglish
Pages (from-to)2247-2256
Number of pages10
JournalProcedia Computer Science
Issue number1
Publication statusPublished - 1 Jan 2015
Externally publishedYes
EventInternational Conference on Computational Science, ICCS 2002 - Amsterdam, Netherlands
Duration: 21 Apr 200224 Apr 2002


  • Cavitation
  • Efficiency
  • Marine propeller design
  • Multi-objective Particle Swarm Optimisation


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