Minmax-Regret Evacuation Planning for Cycle Networks

2019 ◽  
pp. 42-58
Author(s):  
Robert Benkoczi ◽  
Binay Bhattacharya ◽  
Yuya Higashikawa ◽  
Tsunehiko Kameda ◽  
Naoki Katoh
Keyword(s):  
Evacuation Planning ◽  
Minmax Regret

Minmax Regret Maximal Covering Location Problems with Edge Demands

2020 ◽  
pp. 105181
Author(s):  
Marta Baldomero-Naranjo ◽  
Jörg Kalcsics ◽  
Antonio M. Rodríguez-Chía
Keyword(s):  
Location Problems ◽  
Maximal Covering ◽  
Minmax Regret

A fix‐and‐optimize heuristic for the minmax regret shortest path arborescence problem under interval uncertainty

2021 ◽  
Author(s):  
Iago A. Carvalho ◽  
Thiago F. Noronha ◽  
Christophe Duhamel ◽  
Luiz F. M. Vieira ◽  
Vinicius F. dos Santos
Keyword(s):  
Shortest Path ◽  
Interval Uncertainty ◽  
Minmax Regret

scholarly journals Study on Scenario Simulator for Evacuation Planning in Urban Area at Earthquake

2007 ◽  
Vol 24 ◽  
pp. 223-232
Author(s):  
Noboru KIMATA ◽  
Shintaro TERANISHI ◽  
Toru FUTAGAMI
Keyword(s):  
Urban Area ◽  
Evacuation Planning

scholarly journals Combining Computational Fluid Dynamics and Agent-Based Modeling: A New Approach to Evacuation Planning

PLoS ONE ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. e20139 ◽  
Author(s):  
Joshua M. Epstein ◽  
Ramesh Pankajakshan ◽  
Ross A. Hammond
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Agent Based Modeling ◽  
Evacuation Planning ◽  
New Approach ◽  
Agent Based

scholarly journals A New Model for Macroscopic Pedestrian Evacuation Planning with Safety and Duration Criteria

2014 ◽  
Vol 2 ◽  
pp. 486-494 ◽  
Author(s):  
Ismaila Abderhamane Ndiaye ◽  
Emmanuel Neron ◽  
Anais Linot ◽  
Nicolas Monmarche ◽  
Marc Goerigk
Keyword(s):  
Evacuation Planning ◽  
New Model ◽  
Pedestrian Evacuation

Inequalities of Nuclear Risk Communication Within and Beyond the Evacuation Planning Zone

2018 ◽  
Vol 12 (3) ◽  
pp. 587-604
Author(s):  
Xiang Chen ◽  
Clayton Frazier ◽  
Rejina Manandhar ◽  
Zhigang Han ◽  
Peng Jia
Keyword(s):  
Risk Communication ◽  
Evacuation Planning

A Comparison between Agent-Based and GIS-Based Tsunami Evacuation Simulations: A Case Study for Tofino, BC

2021 ◽  
Author(s):  
Joseph Kim ◽  
Tomoyuki Takabatake ◽  
Ioan NISTOR ◽  
Tomoya Shibayama
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Mortality Rates ◽  
Geographical Information ◽  
Evacuation Planning ◽  
Loss Of Life ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Validation Tool

Soft measures such as evacuation planning are recommended to mitigate the loss of life during tsunamis. Two types of evacuation models are widely used: (1) Agent-based modelling (ABM) defines sets of rules that individual agents in a simulation follow during a simulated evacuation. (2) Geographical information systems (GIS) are more accessible to city planners, but cannot incorporate the dynamic behaviours found in ABMs. The two evacuation modelling methodologies were compared through a case study by assessing the state of evacuation preparedness and investigating potential mitigation options. The two models showed different magnitudes for mortality rates and facility demand but had similar trends. Both models agreed on the best solution to reduce the loss of life for the community. GIS may serve as a useful tool for initial investigation or as a validation tool for ABMs. ABMs are recommended for use when modelling evacuation until GIS methodologies are further developed.

scholarly journals A stochastic programming approach for Shelter location and evacuation planning

2018 ◽  
Vol 52 (3) ◽  
pp. 779-805 ◽  
Author(s):  
Vedat Bayram ◽  
Hande Yaman
Keyword(s):  
Stochastic Programming ◽  
Shortest Paths ◽  
Evacuation Planning ◽  
Programming Approach ◽  
Mean Values ◽  
The Road ◽  
Traffic Allocation ◽  
Evacuation Plan ◽  
Allocation Decisions

Shelter location and traffic allocation decisions are critical for an efficient evacuation plan. In this study, we propose a scenario-based two-stage stochastic evacuation planning model that optimally locates shelter sites and that assigns evacuees to nearest shelters and to shortest paths within a tolerance degree to minimize the expected total evacuation time. Our model considers the uncertainty in the evacuation demand and the disruption in the road network and shelter sites. We present a case study for a potential earthquake in Istanbul. We compare the performance of the stochastic programming solutions to solutions based on single scenarios and mean values.

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