Development of rehabilitation plans for water mains replacement considering risk and cost-benefit assessment

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@Article{Giustolisi:2006:CEES,

• author = "Orazio Giustolisi and Daniele Laucelli and Dragan A. Savic",
• title = "Development of rehabilitation plans for water mains replacement considering risk and cost-benefit assessment",
• journal = "Civil Engineering and Environmental Systems",
• year = "2006",
• volume = "23",
• number = "6",
• pages = "175--190",
• note = "Special Issue: Papers selected from the Eighth International Conference on Computing and Control for the Water Industry",
• keywords = "genetic algorithms, genetic programming, Pipe burst modelling, Water mains rehabilitation, Investment/benefit optimisation, Renewal planning",
• ISSN = "1028-6608",
• DOI = "doi:10.1080/10286600600789375",
• size = "16 pages",
• abstract = "The economic and social costs of pipe bursts in water distribution networks (WDNs) are very significant. Water managers need reliable replacement plans for critical pipes, balancing investment with expected benefits in a risk-based management scenario. Thus, a robust and feasible decision support tool for water system rehabilitation is required. This kind of tool should incorporate (i) a model to forecast pipe failures and (ii) a strategy to solve a multi-objective optimisation problem trading investment vs. benefits. The former requires the collection of company asset data and the statistical modelling of pipe bursts. In this article, the burst modelling is performed by the evolutionary polynomial regression technique, providing a symbolic model for predicting pipe bursts. The benefits of burst reduction achieved by mains rehabilitation are evaluated by a multi-objective optimisation model over a short-term planning horizon (taken to be one year in this study). The multi-objective strategy is embedded in a genetic algorithm search methodology. The procedure identifies different subsets of pipes scheduled for rehabilitation, ranging from no-replacement (i.e., no reduction of the predicted number of bursts) to the complete replacement scheme (i.e. maximum reduction of the predicted number of bursts), trading cost of rehabilitation against achieved benefits. The result of the strategy is a Pareto (trade-off) front, which by itself does not provide any prioritisation of pipes for replacement. Thus, the article introduces a further processing step by which pipes are prioritised for rehabilitation based on the number of times each belongs to a solution on the Pareto front. By considering costs and such priority rating of each main, an improved investments/benefit diagram is constructed. The procedure is tested on a real-world UK WDN.",
• notes = "Papers using GP related results",

}

Genetic Programming entries for Orazio Giustolisi Daniele B Laucelli Dragan Savic

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