[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-392500-105":3,"detail-sidebar-cat-1-en-105":81,"doc-detail-392500-en":127},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","a-greedy-double-swap-heuristic-for-nurse-scheduling-paper","A Greedy Double Swap Heuristic for Nurse Scheduling - Paper","","Nurse scheduling involves satisfying numerous hard constraints from regulations and patient demand, while also accounting for staff preferences that add substantial complexity. Many approaches rely on mathematical programming and focus primarily on hard constraints, neglecting nurses’ psychological and preference needs, which can trigger last-minute schedule interventions. A staff-preference optimization framework is proposed using a greedy double swap heuristic, emphasizing fast solution speed and simplicity. Performance is demonstrated via implementation in open source spreadsheet software.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/template/","Template",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/template/presentations/","Presentations",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/template/a-greedy-double-swap-heuristic-for-nurse-scheduling-paper/392500/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/a-greedy-double-swap-heuristic-for-nurse-scheduling-paper/392500.png","ImageObject",442,249,{"name":42,"@type":43},"kopisore","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-18","2026-09-25",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",6,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What problem does the paper address?","Question",{"text":63,"@type":64},"The paper addresses the nurse scheduling problem, focusing on meeting regulatory and patient-driven constraints while incorporating nurses’ preferences.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does the proposed method use greedy double swaps?",{"text":68,"@type":64},"It first applies a greedy swapping algorithm to satisfy hard constraints and reach a feasible sub-space, then uses a second greedy swapping algorithm to optimize soft constraints by minimizing penalty costs.",{"name":70,"@type":61,"acceptedAnswer":71},"How is the method demonstrated experimentally?",{"text":72,"@type":64},"It is implemented using open source spreadsheet software, and performance is reported for both a mock scenario and the original Singapore intensive care unit case.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},392500,1790903511,{"code":4,"msg":82,"data":83},"success",[84,88,93,98,103,108,113,118,123],{"id":85,"doc_module":22,"doc_module_name":25,"category_name":29,"show_sort_weight":86,"slug":87},11,90,"presentations",{"id":89,"doc_module":22,"doc_module_name":25,"category_name":90,"show_sort_weight":91,"slug":92},12,"Resumes",80,"resumes",{"id":94,"doc_module":22,"doc_module_name":25,"category_name":95,"show_sort_weight":96,"slug":97},14,"Invoices",70,"invoices",{"id":99,"doc_module":22,"doc_module_name":25,"category_name":100,"show_sort_weight":101,"slug":102},15,"Posters",60,"posters",{"id":104,"doc_module":22,"doc_module_name":25,"category_name":105,"show_sort_weight":106,"slug":107},16,"Social Media",50,"social-media",{"id":109,"doc_module":22,"doc_module_name":25,"category_name":110,"show_sort_weight":111,"slug":112},17,"Forms",40,"forms",{"id":114,"doc_module":22,"doc_module_name":25,"category_name":115,"show_sort_weight":116,"slug":117},18,"Letters",30,"letters",{"id":119,"doc_module":22,"doc_module_name":25,"category_name":120,"show_sort_weight":121,"slug":122},21,"Paper Templates",5,"papers-templates",{"id":124,"doc_module":22,"doc_module_name":25,"category_name":125,"show_sort_weight":4,"slug":126},158,"General","general-158",{"code":4,"msg":82,"data":128},{"doc_id":79,"user_id":129,"nickname":42,"user_avatar":130,"doc_module":22,"category_id":85,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":131,"file_id":132,"file_url":133,"file_type":134,"file_size":135,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":85,"language":136,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":12,"update_tm":140,"read_time":33},962090880963,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","A Greedy Double Swap Heuristic for Nurse Scheduling  \nMurphy Choy1 and Michelle Cheong  \nSingapore Management University, School of Information System  \n80 Stamford Road, Singapore 178902  \n[Email:](Email: murphychoy@smu.edu.sg)[ ](Email: murphychoy@smu.edu.sg)[murphychoy@smu.edu.sg](Email: murphychoy@smu.edu.sg); [michcheong@smu.edu.sg](michcheong@smu.edu.sg)  \nAbstract  \nOne of the key challenges of nurse scheduling problem (NSP) is the number of constraints placedon preparing the timetable, both from the regulatory requirements as well as the patients’demand for the appropriate nursing care specialists. In addition, the preferences of the nursing staffs related to their work schedules add another dimension of complexity. Most solutions proposed for solving nurse scheduling involve the use of mathematical programming and generally considers only the hard constraints. However, the psychological needs of the nurses are ignored and this resulted in subsequent interventions by the nursing staffs to remedy any deficiency and often results in last minute changes to the schedule. In this paper, we present a staff preference optimization framework which is solved with a greedy double swap heuristic. The heuristic yields good performance in speed at solving the problem. The heuristic is simple and we will demonstrate its performance by implementing it on open source spreadsheet software.  \nKeywords: Nursing Scheduling, Mathematical Programming, Swapping Algorithm, Optimization Framework  \n1.0 Introduction  \nNurse scheduling is a critical issue that many hospitals face in their operations. The main objective of nurse scheduling is to prepare a work schedule that meets manpower needs of the various wards while satisfying the various legislation requirements, as well as workload distribution among the nurses. Very often, the nurses will indicate their individual preferences to the nurse manager who will try to incorporate these preferences within the schedule. Occasionally, some private arrangements were done through nurses’ social networks and informal discussions which further encumber the arrangement process. This makes the entire process iterative and very time consuming.  \nThe nurse scheduling problem is a well explored NP-hard combinatorial optimization problem in literature and there are many researchers who have explored many ways to highlight the plausible solution space (Osogami and Imai, 2000; Brucker [et. al](et. al)., 2010). The early research focused on a scaled down version of the problem that can be solved using mathematical programming techniques (Miller [et. al](et. al)., 1976). These scaled down formulation of the problem are too small  \n1 Corresponding Author.  \nand often ignored too many constraints to be of any practical value. Given the limitations of mathematical programming techniques, many research works branched out into other optimization approaches such as constraint programming (Okada & Okada, 1988), expert system (Chen and Yeung, 1993) and heuristics (Dowsland, 1998; Brusco and Jacobs, 1993; Easton and Mansour, 1993) .  \nExisting literature constructed the objective function based on the information from other literature as well as consultation with the planning staffs. This resulted in the assumption that the objectives of the models have taken care of the preferences of the staffs and thus do not provide for flexibility in the rearrangement of the schedules once they have been created. There are views that the assumption of the models incorporating most of the preferences as a strong one, however, in general, it is not the case. Most importantly, none of the existing literature mentioned about the problem of ad-hoc changes that can occur that necessitate changes to the schedule.  \nThe problem in this paper is highlighted by one of the public hospital in Singapore who is having difficulties in planning their nursing schedule. For this problem, weare examining a schedule involving 15 nurses over a 2-week p","cbCaigJ8K3jj60dH","https://ap.wps.com/l/cbCaigJ8K3jj60dH","pdf",512816,"English","# Abstract\n# 1.0 Introduction\n# 2.0 Background","[{\"question\":\"What problem does the paper address?\",\"answer\":\"The paper addresses the nurse scheduling problem, focusing on meeting regulatory and patient-driven constraints while incorporating nurses’ preferences.\"},{\"question\":\"How does the proposed method use greedy double swaps?\",\"answer\":\"It first applies a greedy swapping algorithm to satisfy hard constraints and reach a feasible sub-space, then uses a second greedy swapping algorithm to optimize soft constraints by minimizing penalty costs.\"},{\"question\":\"How is the method demonstrated experimentally?\",\"answer\":\"It is implemented using open source spreadsheet software, and performance is reported for both a mock scenario and the original Singapore intensive care unit case.\"}]","A Greedy Double Swap Heuristic for Nurse Scheduling - Paper | PDF",1790370454]