Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/313672 
Year of Publication: 
2023
Citation: 
[Journal:] Operations Research Forum [ISSN:] 2662-2556 [Volume:] 4 [Issue:] 4 [Article No.:] 86 [Publisher:] Springer International Publishing [Year:] 2023
Publisher: 
Springer International Publishing
Abstract: 
Abstract Adapting to the consequences of climate change is one of the central challenges faced by humanity in the next decades. One of these consequences are intense heavy rain events, which can cause severe damage to buildings due to flooding. In this paper, we present the first use of optimization techniques that scales well enough to be applicable for supporting decision-making in planning precautionary measures for flash floods caused by heavy rain events in realistic scenarios. Our mixed-integer programming model has been implemented as an innovative decision support tool in the form of a web application, which has already been used by more than 30 engineering offices, municipalities, universities, and other institutions. The model aims to minimize the damage caused in the case of a heavy rain event by taking best-possible actions subject to a limited budget and constraints on the cooperation of residents. We further present an efficient, graph-based representation and preprocessing of the surface terrain, a combinatorial algorithm for computing an initial solution of the mixed-integer program, and computational results obtained on real-word data from different municipalities.
Subjects: 
Mixed-integer programming
Flood mitigation
Graph algorithms
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version
Appears in Collections:

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.