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Research on programmatic multi-attribute decision-making problem: An example of bridge pile foundation project in
Yixuan Lu1, Chunlong Nie1, Denghui Zhou1
1College of Civil Engineering, University of South China, Hengyang, China.
Plos One
|December 4, 2023
Summary
This study optimizes bridge pile foundation selection in karst areas using an improved Analytic Network Process (ANP). The method reduces subjectivity in weight allocation, leading to effective decision-making and high-quality foundations.
Area of Science:
- Civil Engineering
- Geotechnical Engineering
- Decision Science
Background:
- Selecting optimal construction plans for bridge pile foundations in challenging karst geology is critical for project success.
- Existing multi-attribute decision-making methods face challenges with subjective weight allocation and practical implementation.
Purpose of the Study:
- To establish an optimized evaluation framework for selecting pile foundation construction schemes in karst areas.
- To address subjectivity and practical obstacles in multi-attribute decision-making for geotechnical projects.
Main Methods:
- Improved Analytic Network Process (ANP) using directed graph and Bellman-Ford algorithm for subjective weights.
- Dynamic weighting with multiple linear regression to derive universal weights for primary indicators.
- Grey-fuzzy evaluation method for comprehensive scheme scoring and decision-making.
Main Results:
- The improved ANP method demonstrated practical applicability and effective computational results in a case study.
- Universal weights successfully mitigated subjectivity in indicator weight allocation.
- The optimal construction plan resulted in Class I pile foundation quality, validating the model's feasibility.
Conclusions:
- The developed framework provides a robust and objective approach for selecting bridge pile foundation schemes in karst environments.
- Integrating subjective and objective weighting enhances decision-making accuracy and reliability.
- The model's effectiveness is confirmed by achieving superior construction quality in a real-world application.
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