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Development of an integrated decision support method for municipal infrastructure

Horstink, Jordy (2017) Development of an integrated decision support method for municipal infrastructure.

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Abstract:This research presents a method to determine the optimal maintenance activities and maintenance schedule for interrelated roads and sewers resulting in the lowest life cycle cost (LCC), while preserving the minimal required condition of these assets over a predefined period. A literature study has shown that asset managers are increasingly pressured to reduce costs (Danylo, N. and Lemer, A, 1998). This literature also recognizes the need for integrated decision support systems, but recognizes that the focus has been mainly on optimization within single asset types (Shen, Y., and Spainhour, L., 2001). To develop this method a deterministic LCC model was developed that incorporates interrelated roads and sewers. This model uses condition modelling and condition dependent deterioration models to predict the condition of both assets over a 15 year period. The model uses a genetic algorithm because of its robust searching capabilities and possibility to resolve the complexity of large-size optimization problems in an iterative manner. To show the integration capabilities of the model several maintenance methods and corresponding parameters such as their cost are included in the model, allowing for comparison of long term maintenance schedules. The output of the method is a maintenance schedule that prescribes both the maintenance activities and their schedule to reach the lowest possible LCC. This research shows that integration of different asset types into a single model allows for the optimization of the LCC using a genetic algorithm, which can help to overcome departmental fragmentation issues at municipalities. However, further research is needed to enhance the use of condition modelling and algorithm search capabilities.
Item Type:Essay (Master)
Faculty:ET: Engineering Technology
Subject:56 civil engineering
Programme:Civil Engineering and Management MSc (60026)
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