# Systematic Review on the Use of CCPM in Project Management: Empirical Applications and Trends
## 3 Results
A simulated case study involving bridge construction demonstrates its effectiveness, as the project duration was reduced from 163 to 152.5 days, demonstrating gains from optimized buffers and critical sequence reconfiguration based on resource constraints [71]. The next article proposes a hybrid simulation-optimization model for buffer sizing construction projects based on CCPM. The approach combines Monte Carlo analysis, a genetic algorithm (NSGA-II), and a set of performance criteria (such as variance, flexibility, robustness, and complexity) to evaluate multiple buffer alternatives. A case study applied to the construction of a commercial building in Iran demonstrated that the model enables the selection of buffers best suited to the project profile, resulting in greater schedule robustness, more efficient risk control, and reduced schedule deviations [72]. In the next research, a conceptual schedule management model is proposed based on CCPM, incorporating factors such as human behavior, resource constraints, and uncertainty in buffer definition. The method introduces complexity, importance, and risk coefficients to calculate buffers based on triple-point estimates. The model suggests buffer adjustments based on the manager's risk profile. Although not empirically validated, the study makes a valuable contribution by highlighting the influence of decision-maker psychology and proposing formulas for buffers that are more closely aligned with the project's reality [73]. Another study proposes an integrated project control approach that combines the CCM/BM and EVM/ES methods, aiming to monitor time, cost, and risk simultaneously. The methodology, known as the \"efficiency-risk approach,\" incorporates time and cost buffers, along with new formulas for completion estimates. Application to a real project at Mobarakeh Steel Co. demonstrated that the approach allows for more accurate forecasting of completion times and costs, in addition to indicating corrective actions based on buffer consumption [74]. The next paper integrates procurement management with CCPM, introducing resource buffers for piping supplies. Applied to real-world refinery installation cases, the method reduced construction time by approximately 35% compared to traditional CPM. Furthermore, it demonstrated that ignoring supply uncertainty can increase project duration by approximately 5%. The approach provided greater predictability and schedule control, effectively aligning planning and execution [16]. In the study reviewed, an innovative buffer sizing method is proposed based on attribute optimization, simultaneously considering resource constraints and network complexity. The model introduces variables such as resource efficiency, relative cost, and activity start flexibility, applying fuzzy theory and MATLAB simulations. In 500 simulated project runs, the proposed method demonstrated shorter duration (92.73 days) and cost (USD 332,290) compared to traditional methods (C&PM and RSEM) while maintaining a low delay probability (2.6%) and high schedule reliability [75].