Rainfall is regarded as a major uncertainty factor that has adverse impacts on productivity and duration of highway construction activities. In practice, given the location, type, start date, and original duration of the activities, a common approach for construction schedulers to assess the effect of rain is by adding a certain percentage of time to tasks. However, this method depends mainly on the experience and subjective judgment of the schedulers, who may be unfamiliar with the rainfall pattern and its impact on productivity of the operations, and thus, oftentimes produces inaccurate results. This paper presents a model that utilizes historical daily rainfall data and experts' knowledge, and employs fuzzy set concept for assessing the impact of rain on project completion. Based on the model, a fuzzy reasoning knowledge-based scheduling system (FRESS) is proposed. A case study involving a highway construction project implemented in two geographic areas with different rainfall environments is presented to illustrate the salient features of the system that allows users to simulate experts' judgment and to demonstrate the capability and effectiveness of the system that can assist contractors to better estimate activity durations for projects in geographical locations having rainfall data.
All Science Journal Classification (ASJC) codes
- 工程 (全部)