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      Research on emergency material demand based on urgency and satisfaction under public health emergencies

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      PLOS ONE
      Public Library of Science

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          Abstract

          In recent years, the frequent occurrence of public health emergencies has had a significant impact on people’s life. The study of emergency logistics has also attracted scholars’ attention. Therefore, matching emergency materials’ supply and demand quickly, which meets urgency and satisfaction, is the purpose of this paper. This paper used the Metabolism Grey Model (1,1) (GM (1,1)) and the material demand prediction model to predict the number of infections and material demand. Besides, we established a bi-objective optimization model by constructing a profit and loss matrix and a comprehensive utility perception matrix. The results show that the method is helpful in matching the optimal supply and demand decision quickly on the basis of meeting urgency and satisfaction. The method is helpful in improving the fairness of emergency material distribution, which could better protect people’s livelihoods.

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          Most cited references42

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          Emergency Logistics Planning in Natural Disasters

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            A seasonal GM(1,1) model for forecasting the electricity consumption of the primary economic sectors

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              A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: VisualizationRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                23 March 2023
                2023
                23 March 2023
                : 18
                : 3
                : e0282796
                Affiliations
                [001] School of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei, China
                Wuhan University of Technology, CHINA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                [¤]

                Current address: Hebei University of Engineering, Congtai District, Handan, Hebei, China

                Article
                PONE-D-22-31654
                10.1371/journal.pone.0282796
                10035926
                36952544
                473fd815-b95d-4c38-b0a5-a7b12da281ee
                © 2023 Ma et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 November 2022
                : 17 February 2023
                Page count
                Figures: 7, Tables: 9, Pages: 27
                Funding
                Funded by: Social Science Grand Research of the Hebei Education Department
                Award ID: BJ2021070
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 71871084
                This research was funded by the National Natural Science Foundation of China (Grant No. 71871084) and Social Science Grand Research of the Hebei Education Department (Grant No. BJ2021070). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Social Sciences
                Economics
                Economic Models
                Supply and Demand
                Medicine and Health Sciences
                Critical Care and Emergency Medicine
                Medicine and Health Sciences
                Public and Occupational Health
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Optimization
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognitive Psychology
                Decision Making
                Biology and Life Sciences
                Psychology
                Cognitive Psychology
                Decision Making
                Social Sciences
                Psychology
                Cognitive Psychology
                Decision Making
                Biology and Life Sciences
                Neuroscience
                Cognitive Science
                Cognition
                Decision Making
                Medicine and Health Sciences
                Medical Conditions
                Infectious Diseases
                Viral Diseases
                Covid 19
                Computer and Information Sciences
                Information Theory
                Information Entropy
                Custom metadata
                All relevant data are within the paper and its Supporting information files.
                COVID-19

                Uncategorized
                Uncategorized

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