Human Centered Decision-Making for COVID-19 Testing Center Location Selection: Tamil Nadu—A Case Study
Autor: | S. Saroja, R. Madavan, S. Haseena, M. Blessa Binolin Pepsi, Alagar Karthick, V. Mohanavel, M. Muhibbullah |
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Rok vydání: | 2022 |
Předmět: |
Article Subject
General Immunology and Microbiology SARS-CoV-2 Applied Mathematics COVID-19 Computational Biology India General Medicine General Biochemistry Genetics and Molecular Biology COVID-19 Testing Fuzzy Logic Organization and Administration Modeling and Simulation Humans Workplace Algorithms Decision Making Organizational Laboratories Clinical |
Zdroj: | Computational and Mathematical Methods in Medicine. 2022:1-13 |
ISSN: | 1748-6718 1748-670X |
DOI: | 10.1155/2022/2048294 |
Popis: | This paper proposes a blend of three techniques to select COVID-19 testing centers. The objective of the paper is to identify a suitable location to establish new COVID-19 testing centers. Establishment of the testing center in the needy locations will be beneficial to both public and government officials. Selection of the wrong location may lead to lose both health and wealth. In this paper, location selection is modelled as a decision-making problem. The paper uses fuzzy analytic hierarchy process (AHP) technique to generate the criteria weights, monkey search algorithm to optimize the weights, and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to rank the different locations. To illustrate the applicability of the proposed technique, a state named Tamil Nadu, located in India, is taken for a case study. The proposed structured algorithmic steps were applied for the input data obtained from the government of India website, and the results were analyzed and validated using the government of India website. The ranks assigned by the proposed technique to different locations are in aligning with the number of patients and death rate. |
Databáze: | OpenAIRE |
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