|   | 
Details
   web
Records
Author Ahmed Laatabi; Benoit Gaudou; Chihab Hanachi; Patricia Stolf; Sébastien Truptil
Title Coupling Agent-based Simulation with Optimization to Enhance Population Sheltering Type Conference Article
Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022
Volume Issue Pages 116-132
Keywords Sheltering; Simulation; Agent-Based Modeling; Optimization; Vehicle Routing Problem; Coupling; Flood Evacuation
Abstract Population sheltering is a recurrent problem in crisis management that requires addressing two aspects: evacuating vulnerable people using emergency vehicles and regulating movements of pedestrians and individual vehicles towards shelters. While these aspects have received considerable attention in modeling and simulation literature, very few approaches consider them simultaneously. In this paper, we argue that Agent-Based Modeling and Simulation (ABMS) and Optimization are two complementary approaches that can address the problem of sheltering globally and efficiently and be the basis of coherent frameworks for decision- and policy-making. Optimization can build efficient sheltering plans, and ABMS can explore what-if scenarios and use geospatial data to display results within a realistic environment. To illustrate the benefits of a framework based on this coupling approach, we simulate actual flash flood scenarios using real-world data from the city of Trèbes in South France. Local authorities may use the developed tools to plan and decide on sheltering strategies, notably, when and how to evacuate depending on available time and resources.
Address University of Toulouse; University of Toulouse; University of Toulouse; University of Toulouse; CEA Tech Occitanie
Corporate Author Thesis
Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium
Track Analytical Modeling and Simulation Expedition Conference
Notes Approved no
Call Number ISCRAM @ idladmin @ Serial 2403
Share this record to Facebook
 

 
Author Gary Bennett; Lili Yang; Boyka Simeonova
Title A Heuristic Approach to Flood Evacuation Planning Type Conference Article
Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2017
Volume Issue Pages 380-388
Keywords Flood Evacuation Planning; Heuristic; Deterministic; Multi-objective optimization
Abstract Flood evacuation planning models are an important tool used in preparation for flooding events. Authorities use the plans generated by flood evacuation models to evacuate the population as quickly as possible. Contemporary models consider the whole solution space and use a stochastic search to explore and produce solutions. The one issue with stochastic approaches is that they cannot guarantee the optimality of the solution and it is important that the plans be of a high quality. We present a heuristically driven flood evacuation planning model; the proposed heuristic is deterministic, which allows the model to avoid this problem. The determinism of the model means that the optimality of solutions found can be readily verified.
Address School of Business and Economics, Loughborough University, United Kingdom
Corporate Author Thesis
Publisher Iscram Place of Publication Albi, France Editor Tina Comes, F.B., Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN Medium
Track Planning, Foresight and Risk analysis Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management
Notes Approved no
Call Number Serial 2027
Share this record to Facebook
 

 
Author Lili Yang; Qun Liu; Shuang-Hua Yang; Dapeng Yu
Title Evacuation Planning with Flood Inundation as Inputs Type Conference Article
Year 2015 Publication ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2015
Volume Issue Pages
Keywords Dijkstra?s algorithm; flood evacuation planning; Genetic Algorithm (GA); multi-objective optimization
Abstract Recent flooding events happening in our city demonstrate frequency and severity of floods in the UK, highlighting the need to plan and prepare, and efficiently defend. Different from the numerous evacuation model and optimization algorithms, this paper aims to address flood evacuation planning with flood inundation as inputs. A dynamic flooding model and prediction to estimate the development of both surface water and flooding from rivers and watercourses has been fed into evacuation planning at various levels. A three-step approach is proposed. The first step is to identify assembly point designation. The second step is to find the candidate shortest path from each assembly point to all safe areas for all evacuees with consideration of possible inundation. The last step is to determine the optimal safe area for evacuees in the inundation area. The work presented in this paper has emphasized timing issue in evacuation planning. A case study is given to illustrate the use of the approach.
Address
Corporate Author Thesis
Publisher University of Agder (UiA) Place of Publication Kristiansand, Norway Editor L. Palen; M. Buscher; T. Comes; A. Hughes
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9788271177881 Medium
Track Planning, Foresight and Risk Analysis Expedition Conference ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management
Notes Approved yes
Call Number Serial 1299
Share this record to Facebook