Kielhauser, Clemens (2018). A Method for Determining Optimal Intervention Programs for Interrelated Infrastructure Networks (Dissertation, ETH Zürich, D-Baug)
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Cities provide goods and services, such as electric power, gas supply, mobility, water supply and wastewater removal/treatment to the public in order to improve prosperity, quality of living, and opportunities for businesses. These services and goods are distributed via urban infrastructure networks. In order to sustain the provision of service on these networks, interventions have to be executed, that ensure that the state of the objects of the infrastructure network is such that disturbances to the service can be avoided. However, these interventions themselves also cause dis- turbances to the service. Therefore, the task of urban infrastructure management is to balance these two disturbances to find an optimum that fulfils all necessary requirements, such as minimal service level, budget limitations etc. In this thesis, a methodology to determine optimal intervention programs for urban infrastructure networks is presented, that encompasses a suitable deterioration and level of service model while accounting for interactions between networks, and is able to construct intervention programs for multiple infrastructure networks ensemble, with grouping of interventions for multiple time frames. This methodology is set up in a modu- lar way in order to adapt the accuracy to the data input and computational power available. From the scientific point of view, this thesis provides besides the presented methodology also two additional components that are used to 1) group interventions into intervention clusters by applying a dynamic neighbourhood methodology, and 2) measure loss in level of service in a consistent way in order to facilitate the ensemble calculation. The methodology is based on a genetic-algorithms founded optimisation approach. It is found that the methodology is able to calculate intervention programs for multiple infrastructure networks ensemble, with grouping of interven- tions for multiple time frames. The advantages, disadvantages, and future research directions are discussed.
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