Public infrastructure systems are crucial components of modern urban communities as they play major roles in elevating countries’ socio-economics. However, the inherent complexity and systemic interdependence of infrastructure construction/renewal projects have left sites hindered with multiple forms of performance disruptions (e.g., schedule delays, cost overruns, workplace injuries) that result in long-term consequences such as claims, disputes, and stakeholder dissatisfactions. The evolution of advanced data-driven tools (e.g., machine learning and complex network analytics) can play a pivotal role in driving improvements in the management strategies of complex projects due to such tools’ usefulness in applications related to interdependent systems. In this respect, the research presented in this dissertation is aimed at developing data-driven strategies geared towards a resilience-based approach to managing complex infrastructure projects. Such strategies can support project managers and stakeholders with data-informed decision-making to mitigate the impacts of systemic interdependence-induced risks at different levels of their projects. Specifically, the developed data-driven resilience-based strategies can empower decision-makers with the ability to: i) predict potential performance disruptions based on real-time and dynamic project conditions such that proactive response/mitigation strategies and/or contingencies can be deployed ahead of time; and ii) develop adaptive solutions against potential interdependence-induced cascade project disruptions such that rapid restoration of the most important set of performance targets can be restored. It is important to note that data-driven strategies and other analytics-based approaches are not proposed herein to replace but rather to complement the expertise and sensible judgment of project managers and the capabilities of available analysis tools. Specifically, the enriched predictive and analytical insights together with the proactive and rapid adaptation capabilities facilitated by the developed strategies can empower the new paradigm of resilience-guided management of complex dynamic infrastructure projects. / Thesis / Doctor of Philosophy (PhD)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/27222 |
| Date | January 2021 |
| Creators | Gondia, Ahmed |
| Contributors | El-Dakhakhni, Wael, Ezzeldin, Mohamed, Civil Engineering |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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