Buffer management of critical chain projects based on activity dimension differences

As project complexity increases, stricter requirements are imposed on project buffer management. However, existing buffer management approaches primarily consider project attributes while neglecting variations in activity dimension attribute differences, making it difficult to address the differentiated buffering needs among activities and ultimately hindering overall project utility optimization. This study proposes a Dimension-Differentiated Buffer Management (DDBM) method, which refines buffer allocation and monitoring processes to enhance project performance. First, activity attribute indicators are constructed, and the K-means++ clustering algorithm is employed to categorize critical chain activities into subgroups based on dimensional differences, followed by buffer settings and buffer allocation for each subgroup. Second, considering subgroup-level differences, a comprehensive utility coefficient is established to determine buffer distribution among activities. Finally, a dual-level dynamic buffer monitoring mechanism is introduced, incorporating both activity-level and project-level monitoring, based on a qualitative analysis of subgroup-specific buffer demands. The Monte Carlo simulation results demonstrate that the proposed DDBM approach effectively reduces false schedule alarms and achieves an integrated optimization of cost and duration, thereby enhancing buffer monitoring performance. By incorporating activity dimensional differences into buffer management, the proposed model provides decision-makers with an effective tool for managing differentiated buffering needs in complex projects.