Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune-Ant Colony Algorithm
In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm i...
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| Veröffentlicht in: | International journal of environmental research and public health 2020-08, Vol.17 (16), p.5831 |
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| creator | Liu, Ziyuan Li, Zhi Chen, Weiming Zhao, Yunpu Yue, Hanxun Wu, Zhenzhen |
| description | In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony-tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China-considered the first city to suffer from COVID-19-was chosen as an example of verification; the two-level model and the immune algorithm-ant colony optimization-tabu search (IA-ACO-TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies. |
| doi_str_mv | 10.3390/ijerph17165831 |
| format | Article |
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To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.</description><identifier>ISSN: 1660-4601</identifier><identifier>ISSN: 1661-7827</identifier><identifier>EISSN: 1660-4601</identifier><identifier>DOI: 10.3390/ijerph17165831</identifier><identifier>PMID: 32806570</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Algorithms ; Betacoronavirus ; China - epidemiology ; Cities ; Computer simulation ; Cooperation ; Coronavirus Infections - epidemiology ; COVID-19 ; Emergency medical services ; Emergency response ; Environmental assessment ; Environmental impact assessment ; Heuristic ; Hospitals ; Humans ; Integer programming ; Medical research ; Medical Waste Disposal - methods ; Medical wastes ; Neighborhoods ; Optimization ; Optimization algorithms ; Pandemics ; Pneumonia, Viral - epidemiology ; Public Health ; Random variables ; SARS-CoV-2 ; Tabu search ; Traffic congestion ; Transportation - methods ; Transportation - standards ; Travel demand ; Urban Population ; Vehicles ; Verification ; Waste disposal ; Waste storage</subject><ispartof>International journal of environmental research and public health, 2020-08, Vol.17 (16), p.5831</ispartof><rights>2020. 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Li, Zhi ; Chen, Weiming ; Zhao, Yunpu ; Yue, Hanxun ; Wu, Zhenzhen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c418t-6db70a22ad1bcd4b5ff6c005461b5557b4255d85a4e97de9e954416cb4a722a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Betacoronavirus</topic><topic>China - epidemiology</topic><topic>Cities</topic><topic>Computer simulation</topic><topic>Cooperation</topic><topic>Coronavirus Infections - epidemiology</topic><topic>COVID-19</topic><topic>Emergency medical services</topic><topic>Emergency response</topic><topic>Environmental assessment</topic><topic>Environmental impact assessment</topic><topic>Heuristic</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Integer programming</topic><topic>Medical research</topic><topic>Medical Waste Disposal - methods</topic><topic>Medical wastes</topic><topic>Neighborhoods</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Pandemics</topic><topic>Pneumonia, Viral - epidemiology</topic><topic>Public Health</topic><topic>Random variables</topic><topic>SARS-CoV-2</topic><topic>Tabu search</topic><topic>Traffic congestion</topic><topic>Transportation - methods</topic><topic>Transportation - standards</topic><topic>Travel demand</topic><topic>Urban Population</topic><topic>Vehicles</topic><topic>Verification</topic><topic>Waste disposal</topic><topic>Waste storage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Ziyuan</creatorcontrib><creatorcontrib>Li, Zhi</creatorcontrib><creatorcontrib>Chen, Weiming</creatorcontrib><creatorcontrib>Zhao, Yunpu</creatorcontrib><creatorcontrib>Yue, Hanxun</creatorcontrib><creatorcontrib>Wu, Zhenzhen</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>International journal of environmental research and public health</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Ziyuan</au><au>Li, Zhi</au><au>Chen, Weiming</au><au>Zhao, Yunpu</au><au>Yue, Hanxun</au><au>Wu, Zhenzhen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune-Ant Colony Algorithm</atitle><jtitle>International journal of environmental research and public health</jtitle><addtitle>Int J Environ Res Public Health</addtitle><date>2020-08-12</date><risdate>2020</risdate><volume>17</volume><issue>16</issue><spage>5831</spage><pages>5831-</pages><issn>1660-4601</issn><issn>1661-7827</issn><eissn>1660-4601</eissn><abstract>In response to the emergent public health event of COVID-19, the efficiency of transport of medical waste from hospitals to disposal stations is a worthwhile issue to study. In this paper, based on the actual situation of COVID-19 and environmental impact assessment guidelines, an immune algorithm is used to establish a location model of urban medical waste storage sites. In view of the selection of temporary storage stations and realistic transportation demand, an efficiency-of-transport model of medical waste between hospitals and temporary storage stations is established by using an ant colony-tabu hybrid algorithm. In order to specify such status, Wuhan city in Hubei Province, China-considered the first city to suffer from COVID-19-was chosen as an example of verification; the two-level model and the immune algorithm-ant colony optimization-tabu search (IA-ACO-TS) algorithm were used for simulation and testing, which achieved good verification. To a certain extent, the model and the algorithm are proposed to solve the problem of medical waste disposal, based on transit temporary storage stations, which we are convinced will have far-reaching significance for China and other countries to dispatch medical waste in response to such public health emergencies.</abstract><cop>Switzerland</cop><pub>MDPI AG</pub><pmid>32806570</pmid><doi>10.3390/ijerph17165831</doi><orcidid>https://orcid.org/0000-0002-2660-5492</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Betacoronavirus China - epidemiology Cities Computer simulation Cooperation Coronavirus Infections - epidemiology COVID-19 Emergency medical services Emergency response Environmental assessment Environmental impact assessment Heuristic Hospitals Humans Integer programming Medical research Medical Waste Disposal - methods Medical wastes Neighborhoods Optimization Optimization algorithms Pandemics Pneumonia, Viral - epidemiology Public Health Random variables SARS-CoV-2 Tabu search Traffic congestion Transportation - methods Transportation - standards Travel demand Urban Population Vehicles Verification Waste disposal Waste storage |
| title | Path Optimization of Medical Waste Transport Routes in the Emergent Public Health Event of COVID-19: A Hybrid Optimization Algorithm Based on the Immune-Ant Colony Algorithm |
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