A novel MCDM approach for design concept evaluation based on interval-valued picture fuzzy sets

Area of Science:

• Engineering and Technology
• Decision Sciences
• Artificial Intelligence

Background:

• Design concept assessment is crucial for business competitiveness but involves complex, multi-criteria decision-making (MCDM).
• Existing MCDM methods struggle with the inherent uncertainty and ambiguity in evaluating design concepts due to subjective data.
• There is a need for robust methods to handle imprecise information in design evaluation.

Purpose of the Study:

• To develop an enhanced MCDM framework for design concept evaluation that addresses uncertainty and fuzziness.
• To integrate interval-valued picture fuzzy sets (IVPFS) into a comprehensive decision-making process for design concepts.
• To improve the accuracy and reliability of selecting optimal design concepts in complex scenarios.

Main Methods:

• Development of an evaluation indicator system based on literature and expert experience.
• Introduction of interval-valued picture fuzzy numbers (IVPFNs) and the IVPFOWIA operator.
• Application of an entropy weighting method for criteria weighting and an extended TOPSIS approach for alternative selection using IVPFS.

Main Results:

• A novel IVPFS-based MCDM method was successfully developed and applied to design concept evaluation.
• The proposed method demonstrated superior performance in handling complex and uncertain decision-making situations.
• Experiments and comparative analyses confirmed the effectiveness of the IVPFS augmentation in characterizing information ambiguity.

Conclusions:

• The IVPFS combined with improved MCDM techniques offers a powerful solution for design concept evaluation under uncertainty.
• This research provides a scientifically rigorous framework for more reliable and objective selection of design concepts.
• The proposed methodology enhances business decision-making, leading to more market-worthy products.