Advanced Time Buffer Optimization Model for Construction Schedule Management Using Stochastic Analysis

Abstract

Ineffective buffer management within project schedules often leads to delays and increased costs in construction. Conventional methods frequently fail to account for unpredictable, stochastic uncertainties. To address this issue, a stochastic buffer optimization model has been created and tested; it integrates Monte Carlo simulation with critical chain techniques. This model aims to enhance schedule reliability and improve resource allocation. Probability distributions for activity durations were derived from an analysis of data encompassing 167 prior construction projects spanning from 2020 to 2024. Three-parameter lognormal distribution modelling was used. An algorithm optimized multiple objectives, minimizing buffer sizes and delay probabilities, subject to resource limitations. Validation involved implementation in 12 active construction projects. These were in residential, commercial, and infrastructure sectors; performance was monitored over six months. Results were significant. The optimized buffer management system led to a 37% reduction in project delays (p < 0.001). Schedule reliability jumped from 64.7% to 91.8%. Labor (26.8%), equipment (30.1%), and materials (21.7%) all saw substantial improvements in utilization. Buffer utilization efficiency also improved, by 39.3%. Overutilization dropped from 156.3% to 94.8%. The implementation resulted in average cost savings of 8.9% across project types. A strong correlation (r = 0.723, p < 0.001) was found between the Schedule Performance Index and Resource Utilization Efficiency. This validated model can provide project managers with a powerful means of building reliable schedules and optimizing resource allocation, potentially advancing project delivery practices substantially.