Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating

This paper presents a discrete time-space network model for a dynamic resource allocation problem following an epidemic outbreak in a region. It couples a forecasting mechanism for dynamic demand of medical resource based on an epidemic diffusion model and a multistage programming model for optimal...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Mathematical problems in engineering 2015-01, Vol.2015 (2015), p.1-12
Hauptverfasser: Liu, Ming, Xiao, Yihong
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 12
container_issue 2015
container_start_page 1
container_title Mathematical problems in engineering
container_volume 2015
creator Liu, Ming
Xiao, Yihong
description This paper presents a discrete time-space network model for a dynamic resource allocation problem following an epidemic outbreak in a region. It couples a forecasting mechanism for dynamic demand of medical resource based on an epidemic diffusion model and a multistage programming model for optimal allocation and transport of such resource. At each stage, the linear programming solves for a cost minimizing resource allocation solution subject to a time-varying demand that is forecasted by a recursion model. The rationale that the medical resource allocated in early periods will take effect in subduing the spread of epidemic and thus impact the demand in later periods has been incorporated in such recursion model. A custom genetic algorithm is adopted to solve the proposed model, and a numerical example is presented for sensitivity analysis of the parameters. We compare the proposed medical resource allocation mode with two traditional operation modes in practice and find that our model is superior to any of them in less waste of resource and less logistic cost. The results may provide some practical guidelines for a decision-maker who is in charge of medical resource allocation in an epidemics control effort.
doi_str_mv 10.1155/2015/765098
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1685768648</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3639089151</sourcerecordid><originalsourceid>FETCH-LOGICAL-c389t-5275210d44478579873669dd4defd0f74e566861d2a25c9ce2f0a28a985f4f8e3</originalsourceid><addsrcrecordid>eNqF0M1LwzAYBvAgCs7pybsEvIhSl6T56lHm12AyUAeeLKFJtoy2qU3L8L83sx7Ei6e8JD8e8j4AnGJ0jTFjE4IwmwjOUCb3wAgzniYMU7EfZ0Rogkn6dgiOQtggRDDDcgTeF03nKlXCl2JtdF-6egW9hXO_cqFzxe6hbxrfdtD6Fj4Z_X33bILv28LArevW8NZUqtZwVkdSqc75Gi4bHYd6dQwOrCqDOfk5x2B5f_c6fUzmi4fZ9GaeFKnMuoQRwQhGmlIqJBOZFCnnmdZUG6uRFdQwziXHmijCiqwwxCJFpMoks9RKk47BxZDbtP6jN6HLKxcKU5aqNr4POeYxNiZQGen5H7qJu9Txd1FxkWKBKYrqalBF60Nojc2bNvbUfuYY5buu813X-dB11JeDXrtaq637B58NONYWg9UvLCgXOP0CqZ-G6Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1667317140</pqid></control><display><type>article</type><title>Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Wiley-Blackwell Open Access Titles</source><source>Alma/SFX Local Collection</source><creator>Liu, Ming ; Xiao, Yihong</creator><contributor>Lütjen, Michael</contributor><creatorcontrib>Liu, Ming ; Xiao, Yihong ; Lütjen, Michael</creatorcontrib><description>This paper presents a discrete time-space network model for a dynamic resource allocation problem following an epidemic outbreak in a region. It couples a forecasting mechanism for dynamic demand of medical resource based on an epidemic diffusion model and a multistage programming model for optimal allocation and transport of such resource. At each stage, the linear programming solves for a cost minimizing resource allocation solution subject to a time-varying demand that is forecasted by a recursion model. The rationale that the medical resource allocated in early periods will take effect in subduing the spread of epidemic and thus impact the demand in later periods has been incorporated in such recursion model. A custom genetic algorithm is adopted to solve the proposed model, and a numerical example is presented for sensitivity analysis of the parameters. We compare the proposed medical resource allocation mode with two traditional operation modes in practice and find that our model is superior to any of them in less waste of resource and less logistic cost. The results may provide some practical guidelines for a decision-maker who is in charge of medical resource allocation in an epidemics control effort.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2015/765098</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Computer simulation ; Cost analysis ; Decision making ; Demand ; Demand analysis ; Disease control ; Dynamics ; Efficiency ; Epidemics ; Genetic algorithms ; Immunization ; Impact analysis ; Linear programming ; Literature reviews ; Logistics ; Management science ; Mathematical models ; Mathematical problems ; Medical ; Medical wastes ; Monte Carlo simulation ; Optimization ; Ordinary differential equations ; Parameter sensitivity ; Recursion ; Resource allocation ; Resource scheduling ; Sensitivity analysis ; Spreads ; Swine flu ; Traveling salesman problem</subject><ispartof>Mathematical problems in engineering, 2015-01, Vol.2015 (2015), p.1-12</ispartof><rights>Copyright © 2015 Ming Liu and Yihong Xiao.</rights><rights>Copyright © 2015 Ming Liu and Yihong Xiao. Ming Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c389t-5275210d44478579873669dd4defd0f74e566861d2a25c9ce2f0a28a985f4f8e3</citedby><cites>FETCH-LOGICAL-c389t-5275210d44478579873669dd4defd0f74e566861d2a25c9ce2f0a28a985f4f8e3</cites><orcidid>0000-0002-0945-3888 ; 0000-0001-7750-8919</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><contributor>Lütjen, Michael</contributor><creatorcontrib>Liu, Ming</creatorcontrib><creatorcontrib>Xiao, Yihong</creatorcontrib><title>Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating</title><title>Mathematical problems in engineering</title><description>This paper presents a discrete time-space network model for a dynamic resource allocation problem following an epidemic outbreak in a region. It couples a forecasting mechanism for dynamic demand of medical resource based on an epidemic diffusion model and a multistage programming model for optimal allocation and transport of such resource. At each stage, the linear programming solves for a cost minimizing resource allocation solution subject to a time-varying demand that is forecasted by a recursion model. The rationale that the medical resource allocated in early periods will take effect in subduing the spread of epidemic and thus impact the demand in later periods has been incorporated in such recursion model. A custom genetic algorithm is adopted to solve the proposed model, and a numerical example is presented for sensitivity analysis of the parameters. We compare the proposed medical resource allocation mode with two traditional operation modes in practice and find that our model is superior to any of them in less waste of resource and less logistic cost. The results may provide some practical guidelines for a decision-maker who is in charge of medical resource allocation in an epidemics control effort.</description><subject>Computer simulation</subject><subject>Cost analysis</subject><subject>Decision making</subject><subject>Demand</subject><subject>Demand analysis</subject><subject>Disease control</subject><subject>Dynamics</subject><subject>Efficiency</subject><subject>Epidemics</subject><subject>Genetic algorithms</subject><subject>Immunization</subject><subject>Impact analysis</subject><subject>Linear programming</subject><subject>Literature reviews</subject><subject>Logistics</subject><subject>Management science</subject><subject>Mathematical models</subject><subject>Mathematical problems</subject><subject>Medical</subject><subject>Medical wastes</subject><subject>Monte Carlo simulation</subject><subject>Optimization</subject><subject>Ordinary differential equations</subject><subject>Parameter sensitivity</subject><subject>Recursion</subject><subject>Resource allocation</subject><subject>Resource scheduling</subject><subject>Sensitivity analysis</subject><subject>Spreads</subject><subject>Swine flu</subject><subject>Traveling salesman problem</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqF0M1LwzAYBvAgCs7pybsEvIhSl6T56lHm12AyUAeeLKFJtoy2qU3L8L83sx7Ei6e8JD8e8j4AnGJ0jTFjE4IwmwjOUCb3wAgzniYMU7EfZ0Rogkn6dgiOQtggRDDDcgTeF03nKlXCl2JtdF-6egW9hXO_cqFzxe6hbxrfdtD6Fj4Z_X33bILv28LArevW8NZUqtZwVkdSqc75Gi4bHYd6dQwOrCqDOfk5x2B5f_c6fUzmi4fZ9GaeFKnMuoQRwQhGmlIqJBOZFCnnmdZUG6uRFdQwziXHmijCiqwwxCJFpMoks9RKk47BxZDbtP6jN6HLKxcKU5aqNr4POeYxNiZQGen5H7qJu9Txd1FxkWKBKYrqalBF60Nojc2bNvbUfuYY5buu813X-dB11JeDXrtaq637B58NONYWg9UvLCgXOP0CqZ-G6Q</recordid><startdate>20150101</startdate><enddate>20150101</enddate><creator>Liu, Ming</creator><creator>Xiao, Yihong</creator><general>Hindawi Publishing Corporation</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>COVID</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0002-0945-3888</orcidid><orcidid>https://orcid.org/0000-0001-7750-8919</orcidid></search><sort><creationdate>20150101</creationdate><title>Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating</title><author>Liu, Ming ; Xiao, Yihong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c389t-5275210d44478579873669dd4defd0f74e566861d2a25c9ce2f0a28a985f4f8e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Computer simulation</topic><topic>Cost analysis</topic><topic>Decision making</topic><topic>Demand</topic><topic>Demand analysis</topic><topic>Disease control</topic><topic>Dynamics</topic><topic>Efficiency</topic><topic>Epidemics</topic><topic>Genetic algorithms</topic><topic>Immunization</topic><topic>Impact analysis</topic><topic>Linear programming</topic><topic>Literature reviews</topic><topic>Logistics</topic><topic>Management science</topic><topic>Mathematical models</topic><topic>Mathematical problems</topic><topic>Medical</topic><topic>Medical wastes</topic><topic>Monte Carlo simulation</topic><topic>Optimization</topic><topic>Ordinary differential equations</topic><topic>Parameter sensitivity</topic><topic>Recursion</topic><topic>Resource allocation</topic><topic>Resource scheduling</topic><topic>Sensitivity analysis</topic><topic>Spreads</topic><topic>Swine flu</topic><topic>Traveling salesman problem</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Ming</creatorcontrib><creatorcontrib>Xiao, Yihong</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access Journals</collection><collection>CrossRef</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>Middle East &amp; Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</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>Engineering Collection</collection><jtitle>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Ming</au><au>Xiao, Yihong</au><au>Lütjen, Michael</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2015-01-01</date><risdate>2015</risdate><volume>2015</volume><issue>2015</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>This paper presents a discrete time-space network model for a dynamic resource allocation problem following an epidemic outbreak in a region. It couples a forecasting mechanism for dynamic demand of medical resource based on an epidemic diffusion model and a multistage programming model for optimal allocation and transport of such resource. At each stage, the linear programming solves for a cost minimizing resource allocation solution subject to a time-varying demand that is forecasted by a recursion model. The rationale that the medical resource allocated in early periods will take effect in subduing the spread of epidemic and thus impact the demand in later periods has been incorporated in such recursion model. A custom genetic algorithm is adopted to solve the proposed model, and a numerical example is presented for sensitivity analysis of the parameters. We compare the proposed medical resource allocation mode with two traditional operation modes in practice and find that our model is superior to any of them in less waste of resource and less logistic cost. The results may provide some practical guidelines for a decision-maker who is in charge of medical resource allocation in an epidemics control effort.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><doi>10.1155/2015/765098</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-0945-3888</orcidid><orcidid>https://orcid.org/0000-0001-7750-8919</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1024-123X
ispartof Mathematical problems in engineering, 2015-01, Vol.2015 (2015), p.1-12
issn 1024-123X
1563-5147
language eng
recordid cdi_proquest_miscellaneous_1685768648
source Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley-Blackwell Open Access Titles; Alma/SFX Local Collection
subjects Computer simulation
Cost analysis
Decision making
Demand
Demand analysis
Disease control
Dynamics
Efficiency
Epidemics
Genetic algorithms
Immunization
Impact analysis
Linear programming
Literature reviews
Logistics
Management science
Mathematical models
Mathematical problems
Medical
Medical wastes
Monte Carlo simulation
Optimization
Ordinary differential equations
Parameter sensitivity
Recursion
Resource allocation
Resource scheduling
Sensitivity analysis
Spreads
Swine flu
Traveling salesman problem
title Optimal Scheduling of Logistical Support for Medical Resource with Demand Information Updating
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T10%3A03%3A14IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Optimal%20Scheduling%20of%20Logistical%20Support%20for%20Medical%20Resource%20with%20Demand%20Information%20Updating&rft.jtitle=Mathematical%20problems%20in%20engineering&rft.au=Liu,%20Ming&rft.date=2015-01-01&rft.volume=2015&rft.issue=2015&rft.spage=1&rft.epage=12&rft.pages=1-12&rft.issn=1024-123X&rft.eissn=1563-5147&rft_id=info:doi/10.1155/2015/765098&rft_dat=%3Cproquest_cross%3E3639089151%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1667317140&rft_id=info:pmid/&rfr_iscdi=true