Development of a Relative Similarity Degree Based Engineering Construction Multi-Attribute Decision Model and Its...

Area of Science:

• Decision Science
• Engineering Management
• Risk Analysis

Background:

• Multi-attribute decision systems often involve numerous uncertain factors, complicating analysis and strategy.
• Accurate weight extraction for comprehensive indexes is crucial for effective decision-making in complex systems.

Purpose of the Study:

• To develop a novel decision model capable of addressing uncertainty in multi-attribute decision systems.
• To extract index weights using gray relational degree and fuzzy gray relational degree.
• To validate the model's effectiveness and practicality in a real-world scenario.

Main Methods:

• Utilized gray relational degree and fuzzy gray relational degree for weight extraction.
• Developed a new decision model founded on the principle of relative similarity degree.
• Conducted a comparative analysis using maritime safety engineering construction data.

Main Results:

• The developed decision model demonstrated high resolution and sensitivity in multi-attribute decision-making.
• The model proved effective and practical when applied to the case study of maritime safety engineering construction in Hunan Province.
• Weight extraction using fuzzy gray relational degree enhanced the analysis of uncertain factors.

Conclusions:

• The proposed relative similarity degree-based decision model offers a robust solution for multi-attribute decision problems with uncertainty.
• The model's high resolution and sensitivity make it suitable for practical applications in fields like maritime safety.
• This research contributes a valuable tool for improving decision-making processes in complex engineering and management contexts.