Probabilistic Multi-Criteria Decision-Making for Circularity Performance of Modern Methods of Construction Products

2025-04-10

AI Summary

The construction industry urgently requires standardized, uncertainty-aware, and stakeholder-inclusive methods to quantify the circularity of modular and manufactured construction (MMC) products; however, existing assessment approaches lack standardization, struggle with multi-source uncertainties, and fail to reconcile diverse stakeholder perspectives. To address this, we propose the first probabilistic multi-criteria circularity assessment framework specifically designed for MMC products. Our method innovatively integrates Monte Carlo simulation with multi-criteria decision analysis (MCDA), incorporating life cycle data modeling and a hybrid uncertainty characterization—combining expert judgment with empirical measurements—to simultaneously quantify circularity and broader sustainability across technical, economic, and social dimensions. Validated on three real-world MMC products, the framework yields robust, comparable results that significantly enhance the scientific rigor of product selection decisions and strengthen evidence-based policy formulation.

Technology Category

• Machine Learning: Calibration & Uncertainty Quantification
• Reasoning under Uncertainty: Uncertainty Representations
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• User Modeling, Personalization and Recommendation: Metrics for user behavior and evaluating success

Abstract

The construction industry faces increasingly more significant pressure to reduce resource consumption, minimise waste, and enhance environmental performance. Towards the transition to a circular economy in the construction industry, one of the challenges is the lack of a standardised assessment framework and methods to measure circularity at the product level. To support a more sustainable and circular construction industry through robust and enhanced scenario analysis, this paper integrates probabilistic analysis into the coupled assessment framework; this research addresses uncertainties associated with multiple criteria and diverse stakeholders in the construction industry to enable more robust decision-making support on both circularity and sustainability performance. By demonstrating the application in three real-world MMC products, the proposed framework offers a novel approach to simultaneously assess the circularity and sustainability of MMC products with robustness and objectiveness.

Problem

• Lack of standardized framework to measure construction product circularity
• Addressing uncertainties in multi-criteria decision-making for sustainability
• Assessing circularity and sustainability of MMC products robustly

Innovation

• Probabilistic analysis for circularity assessment
• Integrated multi-criteria decision-making framework
• Robust scenario analysis for sustainability