A BWM-TOPSIS based multi-criteria decision-making framework for design of cold patching asphalt binder

This is the authors' abstract. We don't add key points for this paper.

This paper presents an experimental investigation conducted to assess the suitability of a novel multi-criteria decision-making method that integrates the Best-Worst Method (BWM), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and the Taguchi method. This framework was designed to systematically optimize material compositions by adjusting performance characteristic weights and analyzing component ratio effects. To validate the approach, the mix design of a durable cold-patching asphalt (CPA) binder was optimized, with key ratios of light diesel, SEBS, petroleum resin, and silane coupling agent determined to enhance durability. Comprehensive durability assessments identified light diesel as the most influential factor. Comprehensive durability assessments, including adhesion, volatility, storage stability, and evaporation residue tests, identified light diesel as the most influential factor. Comparative mixture experiments demonstrated the superiority of the proposed CPA, exhibiting a 55.7 % increase in final strength and a 23.4 % improvement in high-temperature stability relative to commercial alternatives. The multi-criteria decision-making method (MCDM) framework presented herein offers significant potential for advanced material design, providing a robust, data-driven methodology for performance evaluation and optimization.