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Spatial model for the management of a system of infrastructure facilities
Infrastructure asset management is an important tool that provides decision makers with optimized plans for the maintenance, repair and rehabilitation of systems of infrastructures facilities. The optimization is performed in terms of a limited budget and a pre-defined duration. The first step of th...
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| Format: | Thesis |
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AUC Knowledge Fountain
2014
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| Summary: | Infrastructure asset management is an important tool that provides decision makers with optimized plans for the maintenance, repair and rehabilitation of systems of infrastructures facilities. The optimization is performed in terms of a limited budget and a pre-defined duration. The first step of this thesis was to create three optimization models. First, a standard model that fragments the asset into fractions distributed over the possible conditions to which actions are applied until the assets reach the targeted conditions over the plan's horizon and within budget. Second, was a robust model that assessed the worst case scenario by the integration of uncertainty of the deterioration of the asset. Finally, a Hurwics Criterion model that enhanced the previous models by integrating a level of optimisms to reflect realistic scenarios in which the worst case would not necessarily occur. These models were implemented in a linear and nonlinear integer technique. These models assumed that the asset can be segmented, and then grouped by percentage and assigned to a certain condition. However, in the case of continuous stretches of assets such as pavements, it was noted that this technique does not take into account the distances between the segments of the asset from one another, which was the main challenge this thesis focused on. In order to overcome this gap, a Spatial Model was developed, upgrading the available models to account for the distances. All seven models were then applied on a real case study, which is the Ring Road surrounding Greater Cairo. It was found that the linear integer models have an impact on both the duration of the optimization exercise and the goodness of the final results. Moreover, the Robust Model always gave higher expenses as opposed to the others as it customized itself for the worst case scenario. Furthermore, the Hurwics criterion model once assigned an optimism level different than zero allowed the overall expenses to decrease. Finally, the Spatial model was tested. It included a simulation that was set to give the minimum score and in order to verify the model, the mean and maximum simulations were carried out and as expected they gave higher costs. Finally all seven models were validated through 10 experts that have tested the models. |
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