Evacuating People with Mobility-Challenges in a Short-Notice Disaster

Aruna Apte, Susan K. Heath, Andres Pico, Yong Hui Ronny Tan
<span title="">2015</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jiajcsd7prff7mvjjz6jagt6ai" style="color: black;">Decision Sciences</a> </i> &nbsp;
In past disasters, arrangements have been made to evacuate people without their own transportation, requiring them to gather at select locations to be evacuated. Unfortunately, this type of plan does not help those people who are unable to move themselves to the designated meeting locations. In the United States, according to the Post-Katrina Emergency Management Reform Act of 2006, state or local governments have the responsibility to coordinate evacuation plans for all populations. These
more &raquo; ... de those with disabilities. However, few, if any, have plans in place for those who are mobilitychallenged. The problem of evacuating mobility-challenged people from their individual locations in a short-notice disaster is a challenging combinatorial optimization problem. In order to develop the model and select a solution approach, we surveyed related literature. Based on our review, we formulate the problem and develop an Ant Colony Optimization (ACO) algorithm to solve it. We then test two different versions of the ACO algorithm on five stylized datasets with several different parameter settings.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1111/deci.12153">doi:10.1111/deci.12153</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/g5mcllmvhfflxgu7fbrhr7hf3a">fatcat:g5mcllmvhfflxgu7fbrhr7hf3a</a> </span>
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