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Project scheduling is a complex process involving many types of resources and activities that require optimisation. The resource-constrained project scheduling problem is one of the well-known problematic issues when project activities have to be scheduled to minimise the project duration. Consequently, several methods have been proposed for adjusting the buffer size but none of these traditional methods consider buffer sizing accuracy based on resource constraints. The purpose of this paper is to develop a buffer sizing method based on a fuzzy resource-constrained project scheduling problem in order to obtain an appropriate proportionality between the activity duration and the buffer size. Specifically, a comprehensive resource-constrained method that considers both the general average resource constraints (GARC) and the highest peak of resource constraints (HPRC) is proposed in order to obtain a new buffer sizing method. This paper contributes to the research by considering several different aspects. First, this paper adopts a fuzzy method to calculate and obtain the threshold amount. Second, this paper discusses the resource levelling problem and proposes the HPRC method. Third, the proposed method uses a fuzzy quantitative model to calculate the resource requirement. The findings indicate that the project achieved higher efficiency, providing effective protection and an appropriate buffer size.

A new buffer sizing method based on the uncertainty of the project is proposed in order to improve the accuracy of buffer management. Assuming that the project activities follow lognormal distribution, the model proposed first analyzes the influence of uncertainty, which is characterized as the main factor to affect the activity's duration. Fuzzy theory is then introduced to calculate the uncertainty and is adjusted using resource tightness and network complexity. Finally, a new buffer sizing model based on the uncertainty and the project attributes is introduced. The effectiveness of the method is verified by employing the Monte Carlo simulation, and the actual duration and cost are obtained on the basis of the mean and variance of the project. The experimental results show that the buffer obtained using this method is smaller than the cut and paste method but larger than the root square error method. These findings indicate that the new model is able to avoid the excessive protection issues of the cut and paste method and overcome the root square error method's problem as regards an insufficient consideration of project attributes. The method proposed fully considers the factors that affect buffer sizing, signifying that it can provide the project with effective protection and an appropriate buffer size.

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