Quantitative Risk Assessment Model and Optimization in Infrastructure Fast-Track Construction Projects
Author(s): |
Claudia Garrido Martins
(Department of Engineering Technology and Construction Management, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA)
Susan M. Bogus (Department of Civil, Construction & Environmental Engineering, The University of New Mexico, Albuquerque, NM 87131, USA) Vanessa Valentin (Department of Civil, Construction & Environmental Engineering, The University of New Mexico, Albuquerque, NM 87131, USA) |
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Medium: | journal article |
Language(s): | English |
Published in: | Infrastructures, April 2023, n. 4, v. 8 |
Page(s): | 78 |
DOI: | 10.3390/infrastructures8040078 |
Abstract: |
The construction industry has extensively applied the fast-tracking approach to the demanding need for the fast delivery of infrastructure projects. However, the fast-track strategy might be threatened by distinctive risks or changes in risk characteristics that emerge when activities are overlapped (overlapping risks). This article proposes a risk assessment simulation model to quantify the economic impact of overlapping risks on fast-track infrastructure projects. The model uses Monte Carlo simulation and a proprietary engine solution for the optimization procedure. It quantifies the overlapping risk impacts in the project duration and cost that could originate in three different overlapping degrees and evaluates the optimal overlapping degree to reduce the impact of the overlapping risks. The model demonstration used a commercial renovation project. The results suggest that overlapping risks have a high potential impact on the total cost, although with a high probability of attaining the target duration. Eight top risks affected the total duration, cost, or both. The optimum overlapping to reduce the economic impact and achieve the target project duration combines different overlapping degrees. This study contribution is a model for fast-track projects considering overlapping risks, their impact characteristic as a distribution, and the potential relationship between these risks. |
Copyright: | © 2023 the Authors. Licensee MDPI, Basel, Switzerland. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
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data sheet - Reference-ID
10722693 - Published on:
22/04/2023 - Last updated on:
10/05/2023