![]() The new indicator was used to evaluate the robustness of three baselines generated by different methods but applied to the same case study. The planned start times were obtained from the project baseline generated by each redundancy based method and the real executed start times were obtained from a simulation process based on Monte Carlo technique. The RAD is based in a traditional concept that seeks to minimize the value of the differences between the planned start times and the real executed start times. This indicator called Relative Average Deviation (RAD) is defined as the margin of deviation of the activities’ start times in relation to their durations. In this article a new indicator to analyze the solution robustness to the Project Scheduling Problem with random duration of activities is proposed. These methods add extra time to the original activities duration in order to face the eventualities that may appear during the project execution. ![]() ![]() In this research, three redundancy based methods are evaluated and their performance is compared in terms of robustness. A robust baseline of the project can be obtained from redundancy based methods, which are considered proactive methods to solve the stochastic project scheduling problem. In the Project Scheduling Problem (PSP), the solution robustness can be understood as the capacity that a baseline has to support the disruptions generated by unplanned events (risks). In this vein, this study provides a novel framework for rework management, which offers some insights for researchers and managers. The simulation results illustrate that the ICCDSM method is capable of quantifying and visualizing rework and its impact, decreases iterations, and improves the completion probability. A simulation methodology is used to verify the proposed method. Next, two methods for calculating project buffer are employed. Then potential criticality is proposed to measure the importance of each activity, and the `rework impact area is implicated to indicate potential rework windows. After that, a genetic algorithm is employed to reorder the activity sequence, and a banding algorithm with consideration of resource constraints is used to identify concurrent activities. From the perspective of information flow, the authors firstly make assumptions on activity parameters and interactions between activities. In order to overcome the difficulty in quantifying rework by traditional project schedule management tools, this study proposes an innovative method, namely improved Critical Chain Design Structure Matrix (ICCDSM). The empirical results show that the project schedule generated by the proposed method has a higher on-time completion probability, as well as more appropriately sized project buffers. Finally, we design the max-plus method to generate project schedules and appropriately sized time buffers. Furthermore, the accuracy of time buffers is improved based on the improved rework safety time. We improve the accuracy of the rework safety time in two ways: (1) the overall overlapping effect is taken into consideration when calculating the rework time of an activity arising from the information flow interaction of its multiple predecessors overlapped with it (2) the rework time arising from activity overlaps, the first rework time, and the second rework time are calculated as components of the rework safety time in our model, while the last one is ignored in traditional methods. Our model uses a start-to-start relationship of activities instead of the traditional finish-to-start relationship, which also allows overlaps between activities. To deal with this challenge, we propose a model integrating the critical chain project management method, design structure matrix method, and max-plus method. Rework risks caused by information flow interactions have become a major challenge in project scheduling. ![]()
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