An Algorithmic Framework for Improving the Performance of the Critical Chain Buffer Sizing Method

Delays and disruptions are extremely challenging issues to deal with in project management. In this article, a novel optimization approach to the buffer sizing method is introduced aimed at maximizing the robustness of the buffered schedule generated. The measures affecting the buffer sizing include the network complexity, flexibility, criticality, and robustness. The methodology presented is based on the critical chain project management concept, yet novel metrics are introduced to cover the uncertainties connected with the critical and noncritical chains. The overall purpose of the approach is to investigate the necessity and design of a decision support system to improve the process of critical chain project management. Utilizing a robust and flexible framework, this study tries to efficiently determine the size of feeding and project buffers. The weaknesses of the current critical chain project management approaches were overcome in the critical chain project management, and a new method was developed based on the integration of simulation and optimization techniques. In order to verify the efficiency of the method proposed, a case study is conducted. The outcomes indicate that the robust buffer allocation method proposed yields more stable project schedules, as against the traditional buffer sizing methods.