ModiYacht: intelligent CAD tool for parametric, generative, attributive and interactive modelling of yacht hull forms

Shahroz Khan, Erkan Gunpinar, Kemal Mert Dogan, Bekir Sener, Panagiotis Kaklis

Research output: Contribution to conferencePaperpeer-review

4 Citations (Scopus)
12 Downloads (Pure)


This work proposes ModiYacht, a novel design tool for modelling optimised and customer-centred yacht hull forms. The proposed system incorporates parametric, generative, attribute-based and interactive design models. Parametric modelling uses high-level shape modifiers as quality operators to generate smooth and feasible designs. Because innovative and creative design is essential to a successful product, we also introduce an N-subpopulation-based teaching learning-based optimisation model that generates a variety of solutions to meet user design and performance requirements. Design attributes are developed using machine learning to shorten the communication gap between customers and designers. The generative designs can be used to provide interactive models for customers so that they can fully appreciate the hull-form's features and appearance prior to manufacturing. For this purpose, ModiYacht uses a design-space-shrinking technique during optimisation that guides the exploration process to focus the computational workload on user-preferred options.

Original languageEnglish
Number of pages15
Publication statusPublished - 26 Jun 2022
EventSNAME 14th International Marine Design Conference - Vancouver, Canada
Duration: 26 Jun 202230 Jun 2022


ConferenceSNAME 14th International Marine Design Conference


  • neural network
  • hull
  • optimisation
  • ModiYacht
  • modification
  • machine learning
  • artificial intelligence
  • modifier
  • interface


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