A Multiobjective Variable Neighborhood Strategy Adaptive Search to Optimize the Dynamic EMS Location–Allocation Problem

An aging society increases the demand for emergency services, such as EMS. The more often EMS is needed by patients, the more medical staff are needed. During the COVID-19 pandemic, the lack of medical staff became a critical issue. This research aims to combine the allocation of trained volunteers...

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Bibliographic Details
Main Authors: Ponglert Sangkaphet, Rapeepan Pitakaso, Kanchana Sethanan, Natthapong Nanthasamroeng, Kiatisak Pranet, Surajet Khonjun, Thanatkij Srichok, Sasitorn Kaewman, Chutchai Kaewta
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Computation
Subjects:
Online Access:https://www.mdpi.com/2079-3197/10/6/103
Description
Summary:An aging society increases the demand for emergency services, such as EMS. The more often EMS is needed by patients, the more medical staff are needed. During the COVID-19 pandemic, the lack of medical staff became a critical issue. This research aims to combine the allocation of trained volunteers to substitute for medical staff and solve the EMS relocation problem. The objective of the proposed research is to (1) minimize the costs of the system and (2) maximize the number of people covered by the EMS within a predefined time. A multiobjective variable neighborhood strategy adaptive search (M-VaNSAS) has been developed to solve the problem. From the computational results, it can be seen that the proposed method obtained a better solution than that of current practice and the genetic algorithm by 32.06% and 13.43%, respectively.
ISSN:2079-3197