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Optimizing the Arrangement of Post-Disaster Rescue Activities: An Agent-Based Simulation Approach
Author(s) -
Shuang Chang,
Manabu Ichikawa,
Hiroshi Deguchi,
Yasuhiro Kanatani
Publication year - 2017
Publication title -
journal of advanced computational intelligence and intelligent informatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.172
H-Index - 20
eISSN - 1343-0130
pISSN - 1883-8014
DOI - 10.20965/jaciii.2017.p1202
Subject(s) - computer science , genetic algorithm , set (abstract data type) , emergency rescue , resource allocation , operations research , work (physics) , resource (disambiguation) , risk analysis (engineering) , machine learning , medical emergency , business , medicine , mechanical engineering , computer network , engineering , programming language
This work aims to tackle the following two research questions regarding post-disaster rescues: how to optimize the rescue team dispatch based on the specialties of the team and the type of damage incurred, and how to optimize the allocation of injured patients to hospitals based on their symptoms, the rescue teams allocated, and the abilities of the hospitals to minimize fatalities. Rather than handling these two problems separately, we formulate them into an integrated system. A real-coded genetic algorithm is applied to minimize the estimated transport time in terms of distance, and the disparity between resource supply and demand. A set of scenarios is simulated and analyzed to provide insight for policy makers. Further, the simulated results can be used for future post-disaster medical assistance training.

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