Project risk management is a crucial activity in project management. Nowadays, projects are facing a growing complexity and are thus exposed to numerous and interdependent risks. However, existing classical methods have limitations for modeling the real complexity of project risks. For example, some phenomena like chain reactions and loops are not properly taken into account. This Ph.D. thesis aims at analyzing propagation behavior in the project risk network through modelling risks and risk interactions. An integrated framework of decision support system is presented with a series of proposed methods. The construction of the project risk network requires the involvement of the project manager and the team of experts using the Design Structure Matrix (DSM) method. Simulation techniques are used and several network theory-based methods are developed for analyzing and prioritizing project risks, with respect to their role and importance in the risk network in terms of various indicators. The proposed approach serves as a powerful complement to classical project risk analysis. These novel analyses provide project managers with improved insights on risks and risk interactions under complexity and help them to design more effective response actions. Considering resource constraints, a greedy algorithm and a genetic algorithm are developed to optimize the risk response plan and the allocation of budget reserves dedicated to the risk management. Two examples of application, 1) to a real musical staging project in the entertainment industry and 2) to a real urban transportation system implementation project, are presented to illustrate the utility of the proposed decision support system.
| Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-01018574 |
| Date | 02 December 2011 |
| Creators | Fang, Chao |
| Publisher | Ecole Centrale Paris |
| Source Sets | CCSD theses-EN-ligne, France |
| Language | English |
| Detected Language | English |
| Type | PhD thesis |
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