Research on Emergency Rescue Strategy of Mountain Cross-Country Race

Qianqian Han (), Zhenping Li () and Kang Wang ()
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Qianqian Han: Beijing Wuzi University School of Information
Zhenping Li: Beijing Wuzi University School of Information
Kang Wang: Beijing Wuzi University School of Information

A chapter in LISS 2021, 2022, pp 660-671 from Springer

Abstract: Abstract Due to the long track and poor road conditions of mountain cross-country race, it is easy to happen dangerous situations such as accidental injury of participants. So, this paper studies the location of emergency rescue sites and the allocation of rescue equipment under stochastic demand. According to the road conditions, the track is divided into several segments, and each segment is divided into multiple demand points. For any demand point in each segment, a two-stage stochastic programming model is established with the constraint that the rescuers can arrive in the golden rescue time after sending the distress signal, and the objective function is to minimize the sum of the fixed cost of setting the rescue site, the variable cost of equipping the rescue equipment and the expected rescue cost after the accident, the GUROBI solver and heuristic algorithm are used to solve the problem. Taking the location of rescue sites and the allocation of portable mobile AED as examples, several groups of examples are generated, and the effectiveness of the model is verified by solving the examples. Finally, the results of the examples are analyzed to verify the impact of the segment road conditions and random demand distribution on the emergency rescue site selection and rescue equipment allocation scheme, and the emergency rescue strategy of key monitoring and classified management is put forward. The results of this paper can help the organizers optimize the emergency rescue plan and avoid or reduce the occurrence of accidents.

Keywords: Cross-country race; Rescue site; AED; Stochastic demand; Stochastic programming (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-981-16-8656-6_58

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DOI: 10.1007/978-981-16-8656-6_58

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