Expression and Analysis of Uncertainty in Deep Foundation Pit Design Scheme Decision-Making

The burgeoning urbanization of major cities has precipitated a critical examination of deep foundation pit projects, with escalating costs, protracted construction phases, complex site conditions, and specialized technical requirements. Selecting the optimal design scheme from multiple alternatives in a multiattribute decision-making environment poses a significant challenge. This study presents a novel model tailored for the design of deep foundation pits in design-build (DB) contracting projects. The model combines multiattribute ideal point theory with the analytic hierarchy process to evaluate 22 key factors and their uncertainties. It computes the deviations of potential design schemes from ideal benchmarks across all considered attributes. By employing the lexicographic hierarchy aggregation operator, the model aggregates group-level deviations and linguistically weighted evaluations to calculate a comprehensive score for each design scheme. This approach aids in identifying the most suitable design to meet the deep foundation requirements of DB projects. The effectiveness of the model is demonstrated through its application in the decision-making process for a commercial hotel’s deep foundation pit design scheme. The empirical findings affirm the model’s ability to identify critical factors and accurately assess their impact on engineering design decisions in DB contracting projects. Among the four evaluated designs, the continuous retaining wall scheme achieved the lowest group deviation score, marking it as the preferred option. Consequently, this research offers a robust framework for making informed decisions in the design of deep foundation pits within DB contracting projects, effectively handling the complexities of uncertain linguistic evaluations and the collaboration of multiple attributes.