A Bi-Level Vaccination Points Location Problem That Aims at Social Distancing and Equity for the Inhabitants

Designing efficient vaccination programs that consider the needs of the population is very relevant to prevent reoccurrence of the COVID-19 pandemic. The government needs to provide vaccination points to give out vaccine doses to the population. In this paper, the authors analyze the location of vac...

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Vydáno v:Axioms Ročník 12; číslo 3; s. 305
Hlavní autoři: Salinas, Edith, Camacho-Vallejo, José-Fernando, Nucamendi-Guillén, Samuel
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.03.2023
Témata:
Algorithms
bi-level programming
Control
Coronaviruses
COVID-19
COVID-19 vaccines
cross-entropy metaheuristic
Crowding
Decision making
Disease control
Entropy (Information theory)
Epidemics
Heuristic methods
Immunization
Inhabitants
Mexico
Pandemics
public facility location
Severe acute respiratory syndrome coronavirus 2
Social distancing
Vaccination
vaccination system
Mexico
ISSN:2075-1680, 2075-1680
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Shrnutí:Designing efficient vaccination programs that consider the needs of the population is very relevant to prevent reoccurrence of the COVID-19 pandemic. The government needs to provide vaccination points to give out vaccine doses to the population. In this paper, the authors analyze the location of vaccination points whilst addressing the inhabitants’ preferences. Two objectives that prevent crowding of inhabitants are considered. The government aims for the minimum distance between located vaccination points is maximized, and for the number of inhabitants that attend the different vaccination points to be equitable. One of the key aspects of this problem is the assumption that inhabitants freely choose the located vaccination point to go. That decision affects the objectives of the government, since crowding at vaccination points may appear due to the inhabitants’ decisions. This problem is modeled as a bi-objective, bi-level program, in which the upper level is associated to the government and the lower level to the inhabitants. To approximate the Pareto front of this problem, a cross-entropy metaheuristic is proposed. The algorithm incorporates criteria to handle two objective functions in a simultaneous manner, and optimally solve the lower-level problem for each government decision. The proposed algorithm is tested over an adapted set of benchmark instances and pertinent analysis of the results is included. An important managerial insight is that locating far vaccination points does not lead us to a more equitable allocation of inhabitants.
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ISSN:2075-1680
2075-1680
DOI:10.3390/axioms12030305