Dynamic control for construction project scheduling on-the-run

Dynamic control for construction project scheduling on-the-run

Kammouh, O. (TU Delft System Engineering)
Nogal Macho, M. (TU Delft Integral Design & Management)
Binnekamp, R. (TU Delft Real Estate Management)
Wolfert, A.R.M. (TU Delft Engineering Structures)

Engineering Structures

2022

Construction project management requires dynamic mitigation control to ensure a project's timely completion. Current mitigation approaches are usually performed by an iterative Monte Carlo (MC) analysis which does not reflect (1) the project manager's goal-oriented behavior, (2) contractual project completion performance schemes, and (3) stochastic dependence between construction activities. Therefore, the development statement within this paper is to design a method and implementation tool that properly dissolves all of the aforementioned shortcomings ensuring the project's completion date by finding the most effective and efficient mitigation strategy. For this purpose, the Mitigation Controller (MitC) has been developed using an integrative approach of nonlinear stochastic optimization techniques and probabilistic Monte Carlo analysis. MitC's applicability is demonstrated using a recent Dutch large infrastructure construction project showing its added value for dynamic control on-the-run. It is shown that the MitC is a state-of-the-art decision support tool that a-priori automates and optimizes the search for the best set of mitigation strategies on-the-run rather than a-posteriori evaluating the potentially sub-optimal and over-designed mitigation strategies (as commonly done with modern software such as Primavera P6).

Construction activity correlation
Mitigation control on-the-run
Penalty and reward scheme
Probabilistic time-cost optimization
Stochastic construction scheduling

http://resolver.tudelft.nl/uuid:017e2d08-2db9-4e9d-a1f1-d099fb92d7a9

https://doi.org/10.1016/j.autcon.2022.104450

0926-5805

Automation in Construction, 141

Institutional Repository

journal article

© 2022 O. Kammouh, M. Nogal Macho, R. Binnekamp, A.R.M. Wolfert