چكيده به لاتين
Abstract
Project planning and control is a complex procedure that includes the initial scheduling based on estimations and available resources, and it accounts for measuring the project progress and taking corrective actions in case of disruptions. Normally, the source of the disruptions is the random variations of the activity duration. The research objectives are to link the theoretical background and the application of novel methods of robust project scheduling and intelligent project control based on buffer management procedures. In this thesis, a two-stage multi-objective buffer allocation approach is applied for the robust project scheduling. In the first stage, some decisions are made on the buffer sizes and the allocation to the project activities. A set of Pareto optimal robust schedules are designed through the NSGA II meta-heuristic algorithm based on the decisions made in the buffer allocation step. In the second stage, the Pareto solutions are evaluated in terms of the deviation from the initial start time and due dates. The proposed approach was implemented on a real dam construction project. The outcomes indicated that the obtained buffered schedule reduces the cost of disruptions by 17.7%, as compared with the baseline plan with about 0.3% increase in the project completion time. In addition, a multi-attribute buffer sizing method is developed in order to maximize the project schedule reliability. The attributes concern the network, flexibility, criticality and robustness. Novel metrics are introduced to capture the uncertainties connected with the critical and non-critical chains. Furthermore, a risk quantification procedure is employed to incorporate the external factors into the buffer sizing process. The validation is performed using simulation experiments carried out on the benchmark data test and a real case of a dam construction project. The outcomes indicate that our buffer sizing method results in a more stable plan, as against the traditional buffer sizing methods. In this thesis, 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 non-critical chains. 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.
Keywords: Robust Schedule; Critical Chain Project Management; Project Scheduling; Uncertainty Buffer Sizing
