Research on the Hierarchical Discrete Time-Cost Trade-Off Problem for Program
Publication: Journal of Construction Engineering and Management
Volume 148, Issue 7
Abstract
In an environment of fierce market competition, companies commonly implement several projects simultaneously and employ programs to manage these multiprojects. The program is scheduled at the tactical layer to coordinate multiple projects, each scheduled independently by its project leader. The discrete time-cost trade-off problem (DTCTP) is one of the most significant project scheduling problems, and numerous studies have been conducted on DTCTP for several decades. However, there is still a notable gap in research on DTCTP in multiproject scenarios. A program is a popular approach for managing multiple projects that are related to each other. This paper proposes a new hierarchical discrete time-cost trade-off problem (HDTCTP) for the program that integrates the scheduling problems at the different layers. We clarify the interactions between different layers in program scheduling and introduce the model of a program cascading scheduling process. The program at the upper layer allocates budgets and targets to projects at the lower layer, where each project is scheduled independently. The scheduling results at the lower layer are fed back to the program for further coordination and optimization. This program iteratively coordinates, redistributes budgets, and assigns targets until the overall optimization is achieved. Then the HDTCTP is described and formulated based on analytical target cascading (ATC). To solve the presented HDTCTP, a top-down iterative algorithm is proposed according to the characteristics of HDTCTP in the frame of ATC. A real-life program case verifies the usability of the presented approach, and the results of experiments show that the presented algorithm based on ATC can efficiently solve the presented HDTCTP for programs.
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Data Availability Statement
Data generated or analyzed during the study are available from the corresponding author by request. Information about the journal’s data sharing policy can be found here: http://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001263.
Acknowledgments
This work was supported by the National Natural Science Foundation of China under Grant Nos. 71671117, 71831006, and 71971173 and the Key R & D Program of Shandong under Grant No. 2019JZZY010122.
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Journal of Construction Engineering and Management
Volume 148 • Issue 7 • July 2022
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© 2022 American Society of Civil Engineers.
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Received: Oct 22, 2021
Accepted: Feb 22, 2022
Published online: Apr 18, 2022
Published in print: Jul 1, 2022
Discussion open until: Sep 18, 2022
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