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A hybrid decision support framework for ship design concept evaluation using parsimonious q-ROFS hierarchical multi-criteria decision-making

artificial-intelligence
computer-aided-design
computer-vision
data-mining-and-machine-learning
data-science

Abstract

Design concept evaluation in ship development requires addressing multiple, often conflicting criteria under uncertainty, while maintaining computational efficiency. This study proposes a hybrid Parsimonious q-Rung Orthopair Fuzzy Set Hierarchical Multi-Criteria Decision-Making (PqROFS-HMCDM) framework to facilitate systematic and reliable evaluation across diverse ship types. The framework comprises three stages: (1) construction of a hierarchical indicator system using AIGC-DEMATEL and K-Means clustering to capture interdependencies among criteria; (2) determination of criteria weights via the Parsimonious-q-ROFS-AHP method, balancing cognitive efficiency with robust uncertainty modeling; and (3) comprehensive ranking of design alternatives using q-ROFS-MARCOS according to a new score function. The methodology is demonstrated through a case study of a 42-inch fishing ship, illustrating its ability to handle qualitative and quantitative attributes, model expert judgment uncertainty, and provide consistent rankings. The results confirm the framework’s applicability to various ship types, including commercial vessels and cruise ships, offering a scalable and adaptable decision support tool for early-stage ship design.
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