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          <dc:title>A Bilevel Mixed Integer Linear Programming Model for Valves Location in Water Distribution Systems</dc:title>
          <dc:creator>Peano, Andrea</dc:creator>
          <dc:creator>Nonato, Maddalena</dc:creator>
          <dc:creator>Gavanelli, Marco</dc:creator>
          <dc:creator>Alvisi, Stefano</dc:creator>
          <dc:creator>Franchini, Marco</dc:creator>
          <dc:subject>Isolation Valves Positioning</dc:subject>
          <dc:subject>Bilevel Programming</dc:subject>
          <dc:subject>Hydroinformatics</dc:subject>
          <dc:description>The positioning of valves on the pipes of a Water Distribution System (WDS) is a core decision in the design of the isolation system of a WDS. When closed, valves permit to isolate a small portion of the network, so called a sector, which can be de-watered for maintenance purposes at the cost of a supply disruption. However, valves have a cost so their number is limited, and their position must be chosen carefully in order to minimize the worst-case supply disruption which may occur during pipe maintenance. Supply disruption is usually measured as the undelivered user demand. When a sector is isolated by closing its boundary valves, other portions of the network may become disconnected from the reservoirs as a secondary effect, and experience supply disruption as well. This induced isolation must be taken into account when computing the undelivered demand induced by a sector isolation. While sector topology can be described in terms of graph partitioning, accounting for induced undelivered demand requires network flow modeling. The aim of the problem is to locate a given number of valves at the extremes of the network pipes so that the maximum supply disruption is minimized. We present a Bilevel Mixed Integer Linear Programming (MILP) model for this problem and show how to reduce it to a single level MILP by exploiting duality. Computational results on a real case study are presented, showing the effectiveness of the approach.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Andrea Peano and Maddalena Nonato and Marco Gavanelli and Stefano Alvisi and Marco Franchini</dc:contributor>
          <dc:date>2012</dc:date>
          <dc:relation>Is Part Of OASIcs, Volume 22, 3rd Student Conference on Operational Research (2012)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
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          <dc:identifier>doi:10.4230/OASIcs.SCOR.2012.103</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-35519</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SCOR.2012.103</dc:identifier>
          <dc:language>eng</dc:language>
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