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Fangfang Yu,Xiaobo Chen,Clark A. Cory,Zhixuan Yang,Yingwen Hu 대한토목학회 2021 KSCE JOURNAL OF CIVIL ENGINEERING Vol.25 No.7
Project schedule management is an important aspect of project management. Earned value management (EVM) and its extension methods are widely adopted in project schedule management in various previous studies, however, most of these studies adopted schedule performance indicators based on definiteness condition and historical data, which ignored the impact of uncertainty and dynamics. So the decision risk in schedule management has been increased dramatically. Therefore, this paper proposed an active construction dynamic schedule management model based on fuzzy earned value management (F-EVM) and BP neural network (BP-NN). Firstly, the fuzzy theory was introduced into EVM to evaluate the schedule performance when the project finish schedule cannot be deterministic expression. Then, the main resource planning was functioned as input variables to predict the schedule in advance through BP-NN. Finally, the future action plans was adjusted based on the results to achieve active control of the project schedule. The case results indicated that the introduction of F-EVM effectively reduced influence of subjective estimation on uncertainty in the data measurement process. And the proposed dynamic schedule management model gave a 32.06% better mean absolute percentage error (MAPE) than the existing methods for estimated project duration. Hence, the proposed model provided a more accurate estimation of the project duration and considered the uncertainty and dynamics of the construction project, thereby achieving more effective management of project schedule.
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