# Project Robust Scheduling Based on the Scattered Buffer Technology
## 1 Introduction
Based on the application of buffer time, [PERSON] and [PERSON] set a fuzzy number to determine the model of the compromise schedule, to ensure a better robustness of the schedule after the allocation of resources, and to maintain that the completion time of project is not too long at the same time. In the process of weighing the robustness of activity and the completion time, [PERSON] gave full consideration to the characteristics of activities and stages in the project, and then formulated a balancing scheme of the robustness and the completion time [29; 30]. The size of the time buffer and its regulatory approach directly determine the completion time and the progress risk of the project, which plays a key role in the application of the CC/BM [31]. [PERSON] introduced a new control procedure based on CC/BM, then determined when to expedite which activities in a cost-effective manner, and solved the problem of the neglecting the cost information when taking expediting actions in the most current buffer management (BM) practice [32]. [PERSON] et al. stated that the current buffer supervision mechanism ignores the dynamic characteristics of the project execution and the relative activity information. On the other hand, the scheduling risk analysis (SRA) in the original PERT provided some important information of the key activities that is relative to the project duration. However, these control measures have no close relations with the current project scheduling. In his article, the authors try to study the shortcomings of these two tracking methods, and propose a new monitoring framework for the project scheduling. Some key indexes of activity, such as CRI, are used as important factors to effectively enhance the buffer management [33]. [PERSON] et al. proposed a two-stage multi-objective buffer allocation approach. The purpose of the first stage was to decide the buffer sizes and allocation to the project activities. A set of Pareto-optimal robust schedules was designed by the meta-heuristic non-dominated sorting genetic algorithm (NSGA-II) based on the decisions before. In the second stage, the Pareto solutions were evaluated in terms of the deviation from the initial start time and due dates [34]. To sum up, in the current research achievements of the scattered buffer algorithms, because the metric of the solution robust in various algorithms and the method of determining the buffer size are different, the obtained robustness of the buffer schedule is quite different. Based on the difference of the solution robustness metrics, these algorithms can be divided into two categories: One is based on the parameters reflecting the schedule features, such as the slack between activities, the longest path and the variance of the activity duration, to establish the metric of the robustness to determine the activities that are inserted by the buffers and the size of time buffer. The other is directly based on the deviation between the realized start time of the activity and the predicated start time, and by simulation calculation to choose the size of buffers and the activity that will be inserted by the buffer area. However, this method is mainly subjective to the simulation calculation, so it is necessary to know the information about the random distribution of activity duration in advance. However, sometimes, such uncertain information is difficult to obtain, and, if the estimation is biased, it will directly affect the robustness of the schedule. By analyzing the factors affecting the schedule robustness, this paper is to establish a new metric to measure the solution robustness and to propose a heuristic algorithm based on the time buffers. The structure and contents of this paper are as follows: Section 2 introduces the definition of the solution robustness and the optimal scheduling model of the solution robustness under uncertain environment. This section expounds the idea of the heuristic algorithm for solving the optimal scheduling. Section 3 reviews the existing scattered buffer scheduling algorithms.