Designing a Water Supply Network for Slums in Rio de Janeiro Using Mixed-Integer Programming

Marvin Meck (), Lea Rausch (), John Friesen (), Michael Wurm (), Hannes Taubenböck (), Lena Altherr () and Peter F. Pelz ()
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Marvin Meck: Technische Universität Darmstadt
Lea Rausch: Technische Universität Darmstadt
John Friesen: Technische Universität Darmstadt
Michael Wurm: Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Hannes Taubenböck: Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
Lena Altherr: Technische Universität Darmstadt
Peter F. Pelz: Technische Universität Darmstadt

A chapter in Operations Research Proceedings 2018, 2019, pp 347-354 from Springer

Abstract: Abstract UN Sustainability Development Goal No. 6 aims at ensuring access to water and sanitation for all people by 2030. We address this goal in a multidisciplinary approach by applying mathematical optimisation methods to design optimal water supply systems for underserved areas, such as living environments of the urban poor, which are not integral part of the formal city. Hereby, we use remote sensing data to spatially localise the underserved areas operationalised by typical morphologic indicators for slum areas. With it, slum sizes and locations are spatial information available as input data for the decision problem. This problem is modelled as a MIP and chooses between different approaches combining supply by motorised vehicles with installed pipe systems while minimising overall costs. The solution of this MIP, the design of a low-cost water supply network, is presented and analysed for a slum cluster in Rio de Janeiro.

Keywords: Engineering optimisation; Mixed-integer programming; Sustainable development (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-18500-8_43

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DOI: 10.1007/978-3-030-18500-8_43

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