TY  - CHAP
A1  - Lorenz, Imke-Sophie
A1  - Altherr, Lena
A1  - Pelz, Peter F.
ED  - Neufeld, Janis S.
ED  - Buscher, Udo
ED  - Lasch, Rainer
ED  - Möst, Dominik
ED  - Schönberger, Jörn
T1  - Assessing and Optimizing the Resilience of Water Distribution Systems Using Graph-Theoretical Metrics
T2  - Operations Research Proceedings 2019
N2  - Water distribution systems are an essential supply infrastructure for cities. Given that climatic and demographic influences will pose further challenges for these infrastructures in the future, the resilience of water supply systems, i.e. their ability to withstand and recover from disruptions, has recently become a subject of research. To assess the resilience of a WDS, different graph-theoretical approaches exist. Next to general metrics characterizing the network topology, also hydraulic and technical restrictions have to be taken into account. In this work, the resilience of an exemplary water distribution network of a major German city is assessed, and a Mixed-Integer Program is presented which allows to assess the impact of capacity adaptations on its resilience.
KW  - OR 2019
KW  - business analytics
KW  - decision analytics
KW  - digital economy
KW  - mathematical optimization
Y1  - 2020
SN  - 978-3-030-48439-2
SN  - 978-3-030-48438-5
U6  - http://dx.doi.org/10.1007/978-3-030-48439-2_63
N1  - Annual International Conference of the German Operations Research Society (GOR), Dresden, Germany, September 4-6, 2019
SP  - 521
EP  - 527
PB  - Springer
CY  - Cham
ER  - 
TY  - JOUR
A1  - Rausch, Lea
A1  - Friesen, John
A1  - Altherr, Lena
A1  - Meck, Marvin
A1  - Pelz, Peter F.
T1  - A holistic concept to design optimal water supply infrastructures for informal settlements using remote sensing data
JF  - Remote Sensing
N2  - Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data.
KW  - water supply design
KW  - mathematical optimization
KW  - slum classification
KW  - remote sensing
Y1  - 2018
SN  - 2072-4292
U6  - http://dx.doi.org/10.3390/rs10020216
VL  - 10
IS  - 2
SP  - 1
EP  - 23
PB  - MDPI
CY  - Basel
ER  -