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Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study
<!DOCTYPE html> <!--[if IE 8]> <html class="ie ie8"> <![endif]--> <!--[if IE 9]> <html class="ie ie9"> <![endif]--> <!--[if gt IE 9]><!--> <html> <!--<![endif]--> <head> <meta charset="utf-8" /> <title>Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study</title> <!-- favicon --> <link rel="shortcut icon" type="image/ico" href="./data/ijsom/coversheet/favicon.ico" /> <!-- mobile settings --> <meta name="viewport" content="width=device-width, maximum-scale=1, initial-scale=1, user-scalable=0" /> <!--[if IE]><meta http-equiv='X-UA-Compatible' content='IE=edge,chrome=1'><![endif]--> <!-- user defined metatags --> <meta name="keywords" content="Emergency department,Patient Waiting Time,Patients Scheduling Problem,Genetic Algorithm,Case Study" /> <meta name="description" content="Emergency Departments (EDs) in hospitals typically aim to deliver accurate and rapid treatment to patients. The scheduling of patients in EDs is a challenging task that depends not only on the triage process but also on the availability of both human (staff) and material resources. In this paper, a real case study is conducted to tackle the issues coming from crowding and long waiting times for patients processing at the largest hospital in the region of Sfax (Tunisia). An integer programming formulation is proposed to minimize total patient waiting times (PWT) in EDs subject to procedural and staff availability constraints. Due to the large scale of the treated problem, a Genetic Algorithm (GA) is developed as a solution method. The efficiency of the presented approach is evaluated based on diverse sets of theoretically and randomly generated instances in a first way and on the actual data obtained from the real case study hospital in a second way. Results show significant improvements compared to the First Come First Served (FCFS) real case study鈥檚 rule. The decrease in patient waiting time ranges between 18.84 % to 27.45%." /> <meta name="title" content="Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study" /> <meta name="googlebot" content="NOODP" /> <meta name="citation_title" content="Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study" /> <meta name="citation_author" content="Jlassi, Jih猫ne" /> <meta name="citation_author_institution" content="Route Tunis km 10" /> <meta name="citation_author" content="Rekik, Ines" /> <meta name="citation_author_institution" content="ISGIS" /> <meta name="citation_author" content="Elloumi, Sonda" /> <meta name="citation_author_institution" content="OLID" /> <meta name="citation_author" content="Chabchoub, Habib" /> <meta name="citation_author_institution" content="Al Ain University of Science and Technology" /> <meta name="citation_abstract" content="Emergency Departments (EDs) in hospitals typically aim to deliver accurate and rapid treatment to patients. The scheduling of patients in EDs is a challenging task that depends not only on the triage process but also on the availability of both human (staff) and material resources. In this paper, a real case study is conducted to tackle the issues coming from crowding and long waiting times for patients processing at the largest hospital in the region of Sfax (Tunisia). An integer programming formulation is proposed to minimize total patient waiting times (PWT) in EDs subject to procedural and staff availability constraints. Due to the large scale of the treated problem, a Genetic Algorithm (GA) is developed as a solution method. The efficiency of the presented approach is evaluated based on diverse sets of theoretically and randomly generated instances in a first way and on the actual data obtained from the real case study hospital in a second way. Results show significant improvements compared to the First Come First Served (FCFS) real case study鈥檚 rule. The decrease in patient waiting time ranges between 18.84 % to 27.45%." /> <meta name="citation_id" content="2914" /> <meta name="citation_publication_date" content="2023/11/01" /> <meta name="citation_date" content="2023-11-01" /> <meta name="citation_journal_title" content="International Journal of Supply and Operations Management" /> <meta name="citation_issn" content="23831359" /> <meta name="citation_volume" content="10" /> <meta name="citation_issue" content="4" /> <meta name="citation_firstpage" content="439" /> <meta name="citation_lastpage" content="455" /> <meta name="citation_publisher" content="Kharazmi University" /> <meta name="citation_doi" content="10.22034/ijsom.2023.109945.2766" /> <meta name="DC.Identifier" content="10.22034/ijsom.2023.109945.2766" /> <meta name="citation_abstract_html_url" content="http://www.ijsom.com/article_2914.html" /> <meta name="citation_pdf_url" content="http://www.ijsom.com/article_2914_d7bd0820a1898fc73482fb3c277775e8.pdf" /> <meta name="DC.Title" content="Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study" /> <meta name="DC.Source" content="International Journal of Supply and Operations Management" /> <meta name="DC.Date" content="01/11/2023" /> <meta name="DC.Date.issued" content="2023-11-01" /> <meta name="DC.Format" content="application/pdf" /> <meta name="DC.Contributor" content="Jlassi, Jih猫ne" /> <meta name="DC.Contributor" content="Rekik, Ines" /> <meta name="DC.Contributor" content="Elloumi, Sonda" /> <meta name="DC.Contributor" content="Chabchoub, Habib" /> <meta name="og:title" content="Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study" /> <meta name="og:description" content="Emergency Departments (EDs) in hospitals typically aim to deliver accurate and rapid treatment to patients. The scheduling of patients in EDs is a challenging task that depends not only on the triage process but also on the availability of both human (staff) and material resources. In this paper, a real case study is conducted to tackle the issues coming from crowding and long waiting times for patients processing at the largest hospital in the region of Sfax (Tunisia). An integer programming formulation is proposed to minimize total patient waiting times (PWT) in EDs subject to procedural and staff availability constraints. Due to the large scale of the treated problem, a Genetic Algorithm (GA) is developed as a solution method. The efficiency of the presented approach is evaluated based on diverse sets of theoretically and randomly generated instances in a first way and on the actual data obtained from the real case study hospital in a second way. Results show significant improvements compared to the First Come First Served (FCFS) real case study鈥檚 rule. 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in Emergency Department: A Case Study</span></h1> <div> <div class="margin-bottom-3"> </div> <p class="margin-bottom-3">Document Type : TORS 2022</p> <p class="padding-0" style="margin:12px -2px 0 -2px"><strong>Authors</strong></p> <ul class="list-inline list-inline-seprator margin-bottom-6 ltr"> <li class="padding-3"> <a href="./?_action=article&au=129989&_au=Jih%C3%A8ne++Jlassi">Jihène Jlassi</a> <sup><a href="#aff1" >1</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=130184&_au=Ines++Rekik">Ines Rekik</a> <sup><a href="mailto:ines.rekik@isgis.usf.tn" data-toggle="tooltip" data-placement="bottom" title="Email to Corresponding Author"><i class="fa fa-envelope-o" ></i></a></sup> <sup><a href="#aff2" >2</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=130185&_au=Sonda++Elloumi">Sonda Elloumi</a> <sup><a href="#aff3" >3</a></sup> </li> <li class="padding-3"> <a href="./?_action=article&au=130010&_au=Habib++Chabchoub">Habib Chabchoub</a> <sup><a href="#aff4" >4</a></sup> </li> </ul> <p class="margin-bottom-3 ltr" id="aff1"> <sup>1</sup> Route Tunis km 10 </p> <p class="margin-bottom-3 ltr" id="aff2"> <sup>2</sup> ISGIS </p> <p class="margin-bottom-3 ltr" id="aff3"> <sup>3</sup> OLID </p> <p class="margin-bottom-3 ltr" id="aff4"> <sup>4</sup> Al Ain University of Science and Technology </p> <div class="margin-bottom-3 ltr" id="ar_doi" title="DOI"><i class="ai ai-doi size-25 text-orange"></i> <span dir="ltr"><a href="https://dx.doi.org/10.22034/ijsom.2023.109945.2766">10.22034/ijsom.2023.109945.2766</a></span></div> <p style="margin:12px -2px 0 -2px"><strong>Abstract</strong></p> <div class="padding_abstract justify ltr">Emergency Departments (EDs) in hospitals typically aim to deliver accurate and rapid treatment to patients. The scheduling of patients in EDs is a challenging task that depends not only on the triage process but also on the availability of both human (staff) and material resources. In this paper, a real case study is conducted to tackle the issues coming from crowding and long waiting times for patients processing at the largest hospital in the region of Sfax (Tunisia). An integer programming formulation is proposed to minimize total patient waiting times (PWT) in EDs subject to procedural and staff availability constraints. Due to the large scale of the treated problem, a Genetic Algorithm (GA) is developed as a solution method. The efficiency of the presented approach is evaluated based on diverse sets of theoretically and randomly generated instances in a first way and on the actual data obtained from the real case study hospital in a second way. Results show significant improvements compared to the First Come First Served (FCFS) real case study’s rule. The decrease in patient waiting time ranges between 18.84 % to 27.45%.</div> <p class="padding-0" style="margin:12px -2px 0 -2px"><strong>Keywords</strong></p> <ul class="block list-inline list-inline-seprator margin-bottom-6 ltr"> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106431&_kw=Emergency+department" >Emergency department</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106432&_kw=Patient+Waiting+Time" >Patient Waiting Time</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=106433&_kw=Patients+Scheduling+Problem" >Patients Scheduling Problem</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=102135&_kw=Genetic+Algorithm" >Genetic Algorithm</a> </li> <li class="padding-3"> <a class="tag_a" href="./?_action=article&kw=104691&_kw=Case+Study" >Case Study</a> </li> </ul> </div> <hr> <div class="page_break"></div> <div class="panel"> <div class="panel-heading card-header"> <h4 class="panel-title "> <a data-toggle="collapse" data-parent="#accordions" href="#collapsesRef"><i class="fa fa-plus"></i> References</a> </h4> </div> <div id="collapsesRef" class="panel-collapse collapse"> <div class="panel-body justify"> <div class="padding-3 margin-top-3 ltr justify">Abdalkareem Z.A., Amir A., Azmi Al鈥態etar M., Ekhan P. and Hammouri A.I. 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Chaotic genetic algorithm and adaboost ensemble metamodeling approach for optimum resource planning in emergency departments. <em>Artificial Intelligence in Medicine</em>, Vol. 84, pp. 23–33. </div> <div class="padding-3 margin-top-3 ltr justify">Zachariasse J.M., Nieboer D., Oostenbrink R., Moll H.A. and Steyerberg E.W. (2018). Multiple performance measures are needed to evaluate triage systems in the emergency department. <em>Journal of Clinical Epidemiology</em>, Vol. 94, pp. 27-34. </div> <div class="padding-3 margin-top-3 ltr justify">Zhang A., Zhu X., Lu Q. and Zhang R. (2019). Impact of Prioritization on the Outpatient Queuing System in the Emergency Department with Limited Medical Resources. <em>Symmetry</em>, Vol. 11(6), 796.</div> </div> </div> </div> </div> </div> <!-- /CENTER --> <!-- LEFT --> <div class="col-lg-3 col-md-3 col-sm-4"> <div class="panel panel-default my_panel-default margin-bottom-10"> <div class="panel-body ar_info_pnl" id="ar_info_pnl_cover"> <div id="pnl_cover"> <div class="row" > <div class="col-xs-6 col-md-6 nomargin-bottom"> <a href="javascript:loadModal('International Journal of Supply and Operations Management', './data/ijsom/coversheet/cover_en.jpg')"> <img src="data/ijsom/coversheet/cover_en.jpg" alt="International Journal of Supply and Operations Management" style="width: 100%;"> </a> </div> <div class="col-xs-6 col-md-6 nomargin-bottom"> <h6><a href="./issue_536_541.html">Volume 10, Issue 4</a><br/>November 2023<div id="sp_ar_pages">Pages <span dir="ltr">439-455</span></div></h6> </div> </div> </div> </div> </div> <!-- 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Rekik, I., Elloumi, S., & Chabchoub, H. (2023). Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study. <em>International Journal of Supply and Operations Management</em>, 10(4), 439-455. doi: 10.22034/ijsom.2023.109945.2766</p> </div> </div> </div> </div> <div id="cite-mla" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content"> <!-- Modal Header --> <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">MLA</h4> </div> <!-- Modal Body --> <div class="modal-body"> <p>Jihène Jlassi; Ines Rekik; Sonda Elloumi; Habib Chabchoub. "Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study". <em>International Journal of Supply and Operations Management</em>, 10, 4, 2023, 439-455. doi: 10.22034/ijsom.2023.109945.2766</p> </div> </div> </div> </div> <div id="cite-harvard" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content"> <!-- Modal Header --> <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">HARVARD</h4> </div> <!-- Modal Body --> <div class="modal-body"> <p>Jlassi, J., Rekik, I., Elloumi, S., Chabchoub, H. (2023). 'Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study', <em>International Journal of Supply and Operations Management</em>, 10(4), pp. 439-455. doi: 10.22034/ijsom.2023.109945.2766</p> </div> </div> </div> </div> <div id="cite-vancouver" class="modal fade" tabindex="-1" role="dialog" aria-labelledby="myModalLabel" aria-hidden="true"> <div class="modal-dialog"> <div class="modal-content"> <!-- Modal Header --> <div class="modal-header"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> <h4 class="modal-title" id="myModalLabel">VANCOUVER</h4> </div> <!-- Modal Body --> <div class="modal-body"> <p>Jlassi, J., Rekik, I., Elloumi, S., Chabchoub, H. Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study. <em>International Journal of Supply and Operations Management</em>, 2023; 10(4): 439-455. doi: 10.22034/ijsom.2023.109945.2766</p> </div> </div> </div> </div> </div> </div> <!-- /MAIN CONTENT --> <!-- Subscribe --> <section class="alternate padding-xxs"> </section> <!-- /Subscribe --> <!-- FOOTER --> <div class="container"> <footer id="footer"> <div class="scrollup" id="scroll" href="#"><span></span></div> <div class="row"> <div class="col-md-2"> <!-- Links --> <h4 class="">Explore Journal</h4> <ul class="footer-links list-unstyled"> <li id="fli_home"><a href="./">Home</a></li> <li id="fli_about"><a href="./journal/about">About Journal</a></li> <li id="fli_Edb"><a href="./journal/editorial.board">Editorial Board</a></li> <li id="fli_submit"><a href="./author">Submit Manuscript</a></li> <li id="fli_contactus"><a href="./journal/contact.us">Contact Us</a></li> <li id="fli_glossary"><a href="./journal/glossary">Glossary</a></li> <li id="fli_order_hrdj"><a href="./journal/subscription.form">Hard Copy Subscription</a></li> <li id="fli_sitemap"><a href="./sitemap.xml?usr">Sitemap</a></li> </ul> <!-- /Links --> </div> <div class="col-md-3"> <!-- Latest News --> <h4 class="">Latest News</h4> <ul class="footer-posts list-unstyled"> <li> <a href="./news?newsCode=173">SD of ISC: Sustainable Development of Intelligent Supply Chains based on Trends and Future Directions: Application of Novel Solution Techniques</a> <small class="ltr">2023-03-05</small> </li> </ul> <!-- /Latest News --> </div> <div class="col-md-3"> <!-- Footer Note --> <div><p><a title="Linkedin" href="http://www.linkedin.com/company/ijsom?trk=eml-cp_mktg-btn-welcome-20120607%2F"><img src="images/linkedin.jpg" alt="linkedin" /></a></p></div> <!-- /Footer Note --> </div> <div class="col-md-4"> <!-- Newsletter Form --> <h4 class="">Newsletter Subscription</h4> <p>Subscribe to the journal newsletter and receive the latest news and updates</p> <form class="validate" action="" method="post" data-success="Subscription saved successfully." data-toastr-position="bottom-right"> <input type="hidden" name="_token" value="b0be9a4d892b6758cbbc53779cdb4760088a1223e37cb995"/> <div class="input-group"> <span class="input-group-addon"><i class="fa fa-envelope"></i></span> <input type="email" id="email" name="email" required="required" class="form-control required sbs_email" placeholder="Enter your Email" oninvalid="this.setCustomValidity('Enter a valid email address.')" oninput="this.setCustomValidity('')"> <span class="input-group-btn"> <button class="btn btn-primary mybtn" type="submit">Subscribe</button> </span> </div> </form> <!-- /Newsletter Form --> <!-- Social Icons --> <div class="margin-top-20"> <a class="noborder" href="" target="_blank" class="social-icon social-icon-border social-facebook pull-left block" data-toggle="tooltip" data-placement="top" title="Facebook"> <i class="fa fa-facebook-square" aria-hidden="true"></i> </a> <a class="noborder" href="" target="_blank" class="social-icon social-icon-border social-facebook pull-left block" data-toggle="tooltip" data-placement="top" title="Twitter"> <i class="fa fa-twitter-square" aria-hidden="true"></i> </a> <a class="noborder" href="" target="_blank" class="social-icon social-icon-border social-facebook pull-left block" data-toggle="tooltip" data-placement="top" title="Linkedin"> <i class="fa fa-linkedin-square" aria-hidden="true"></i> </a> <a class="noborder" href="./ju.rss" class="social-icon social-icon-border social-rss pull-left block" data-toggle="tooltip" data-placement="top" title="Rss"><i class="fa fa-rss-square" aria-hidden="true"></i></a> </div> </div> </div> <div class="copyright" style="position: relative"> <ul class="nomargin list-inline mobile-block"> <li>© Journal Management System. <span id='sp_crt'>Powered by <a target='_blank' href='https://www.sinaweb.net/'>Sinaweb</a></span></li> </ul> </div> </footer> </div> <!-- /FOOTER --> </div> <!-- /wrapper --> <!-- SCROLL TO TOP --> <a href="#" id="toTop_old"></a> <!-- PRELOADER --> <div id="preloader"> <div class="inner"> <span class="loader"></span> </div> </div><!-- /PRELOADER --> <!-- JAVASCRIPT FILES --> <script type="text/javascript">var plugin_path = './themes/base/front/assets/plugins/';</script> <script type="text/javascript" src="./themes/base/front/assets/js/scripts.js?v=0.02"></script> <!-- user defined scripts--> <!-- Extra Script Scripts --> <script type="text/javascript"> $('ul.nav li.dropdown').hover(function() { if (window.matchMedia('(max-width: 767px)').matches) return; 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