Bundling strategies for routine expressway maintenance projects with similarity thresholds

This study explored the bundling of routine expressway maintenance projects by utilizing project similarity to achieve economies of scale. Although existing studies have introduced methods for measuring similarity, limited theoretical research has addressed the issue of the optimal bundling scale across different project types. To fill this gap, this study developed a bundling decision-making model based on combinatorial optimization theory and designed a greedy algorithm for its solution. By introducing a similarity threshold, bundling schemes with varying levels of similarity were generated, and evaluation indicators are proposed to assess their effectiveness. A case study of 41 expressway maintenance segments under the jurisdiction of the Provincial Expressway Group Company was conducted to validate the model. The results indicate that different similarity thresholds lead to significantly distinct bundling schemes, requiring a comprehensive consideration of management needs, market competition, and contract execution capacity. The findings suggest that an optimal scheme should strike a balance between economies of scale and management coordination, with expert adjustments made when necessary. This study adds to the body of knowledge by introducing a novel quantitative framework and solution approach for project bundling decisions, providing valuable implications for improving resource allocation efficiency and economic performance.