[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-308696-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-308696-en":130},{"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","improving-customer-waiting-time-at-a-dmv-center-using-discrete-event-simulation","Improving Customer Waiting Time at a DMV Center Using Discrete-Event Simulation","","Virginia's Department of Motor Vehicles (DMV) faces major delays driven by excessively large customer arrival rates, leading to long queues that may extend beyond the building and generate complaints. This study builds a discrete-event simulation (DES) model of a DMV center, using data collected from experts at the DMV headquarters in Richmond and implemented in Arena 10.0. The model is verified and validated, identifies key delay causes, and tests statistical significance for two enhancement scenarios to reduce customer waiting time by targeting ticketing, service-window, and transaction delays.",{"@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/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/improving-customer-waiting-time-at-a-dmv-center-using-discrete-event-simulation/308696/",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/improving-customer-waiting-time-at-a-dmv-center-using-discrete-event-simulation/308696.png","ImageObject",300,407,{"name":42,"@type":43},"Mali","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-21","2026-09-20",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",8,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What simulation approach is used to model the DMV center?","Question",{"text":63,"@type":64},"The study uses Discrete Event Simulation (DES) to model DMV operations progressing in discrete, non-continuous time steps.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does the model represent the customer flow and queues?",{"text":68,"@type":64},"Customers first join a check-in (ticketing) queue, then proceed to one of 10 available service windows in FIFO order, with separate M/M/1 queues modeled for each window.",{"name":70,"@type":61,"acceptedAnswer":71},"Which delay components does the study focus on reducing?",{"text":72,"@type":64},"The study targets three delays: ticketing waiting time, service-window waiting time, and transaction time (time spent being serviced).","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},308696,1790192639,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,111,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":55,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":97,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144,"preview_page_count":4},2336475104362,"https://ap-avatar.wpscdn.com/avatar/22000c4c46a41b752dd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786595829695023868","# 1.INTRODUCTION\n\nThe usage of simulation has increased noticeablyin the recent years due to the advancement ofcomputer technology.  The act of simulatingbehaviors and situations has been adopted inmultiple areas like military,social behavior,flightsimulators,robotics,etc.In this paper,we useDiscrete Event Simulation(DES)since our aim ismodeling the DMV system as it progresses overdiscrete times in a non-continuous fashion.In thismodel,we attempt to mimic the behavior of thereal DMV center system by building our modelfrom variables that are generated from data that iscollected from experts of the DMV headquarter inRichmond,VA.The model is examined thoroughlyand conclusions and solutions are produced fromthis study.Additionally,the study identifies twopossible scenarios to enhance the system,anddetermines if they present a statistical significanceto the model.  \n## 1.1 OBJECTIVES OF THE STUDY\n\nThe study is conducted in order to(1)minimize thecustomer waiting time at the DMV-850 Widgeon  \nImproving Customer Waiting Time at a DMV Center UsingDiscrete-Event Simulation  \nGeorges M.Arnaout(Ph.D.Student)*;Shannon Bowling(Ph.D.)Engineering Management and Systems Engineering-Old Dominion University(Norfolk,VA)garna001@odu.edu  \nAbstract.Virginia's Department of Motor Vehicles (DMV)serves a customer base of approximately 5.6 millionlicensed drivers and ID card holders and 7 million registered vehicle owners.DMV has more daily face-to-facecontact with Virginia's citizens than any other state agency [1].The DMV faces a major dificulty in keeping upwith the excessively large customers'arrival rate.The consequences are queues building up,stretching out tothe entrance doors(and sometimes even outside)and customers complaining.  While the DMV stateemployees are trying to serve at their fastest pace,the remarkably large queues indicate that there is a seriousproblem that the DMV faces in its services,which must be dealt with rapidly.Simulation is considered as oneof the best tools for evaluating and improving complex systems.In this paper,we use it to model one of theDMV centers located in Norfolk,VA.The simulation model is modeled in Arena 10.0 from Rockwell systems.The data used is collected from experts of the DMV Virginia headquarter located in Richmond.The modelcreated was verified and validated.The intent of this study is to identify key problems causing the delays atthe DMV centers and suggest possible solutions to minimize the customers'waiting time.In addition,twotentative hypotheses aiming to improve the model's design are tested and validated.  \nRoad,Norfolk,(2)give insights towards minimizingthe customer waiting time at all the DMV centers,statewide,or around the country,(3)attempt toimprove the existing model (i.e.Should we addanother check-in window?),and (4)givesuggestions aiming for optimizing the system.Thefocus of the study will be on reducing the followingthree delays:1-The ticketing waiting time:timeneeded to obtain a service ticket.2-The servicewindow waiting time:time needed to reach theservice window and be serviced.   3-Thetransaction time:time needed to be serviced.  \n## 2.0 THE MODEL\n\nThe model built using Arena(version 10)fromRockwell Systems,is a miniature of the existingDMV center located at 850 Widgeon Rd,Norfolk,VA.  \n## 2.1 Model Details\n\nCustomers arrive in a stochastic way according toan inter-arrival rate produced by exhaustiveobservations conducted at the Widgeon center.The model has a main queue called the “check-in”  \nqueue.This is the main queue where all customershave to pass through in order to get their ticketsand proceed to the nearby seating area,waiting fortheir ticket number to be announced.When acustomer's ticket number is announced,thecustomer proceeds to one of the service windowsin order to be served in a FIFO manner.As thereare 14 service windows,according to our extensiveobservations,only 10 windows are being used atthe same time.Thus,for the sake of the study,weconsider 10 windows with 10 se","cbCaiceVEHMa8sbf","https://ap.wps.com/l/cbCaiceVEHMa8sbf","pdf",2757772,"English","# 1. Introduction\n## 1.1 Objectives of the Study\n# 2.0 The Model\n## 2.1 Model Details\n## 2.2 Model Constraints","[{\"question\":\"What simulation approach is used to model the DMV center?\",\"answer\":\"The study uses Discrete Event Simulation (DES) to model DMV operations progressing in discrete, non-continuous time steps.\"},{\"question\":\"How does the model represent the customer flow and queues?\",\"answer\":\"Customers first join a check-in (ticketing) queue, then proceed to one of 10 available service windows in FIFO order, with separate M/M/1 queues modeled for each window.\"},{\"question\":\"Which delay components does the study focus on reducing?\",\"answer\":\"The study targets three delays: ticketing waiting time, service-window waiting time, and transaction time (time spent being serviced).\"}]","Improving Customer Waiting Time at a DMV Center Using Discrete-Event Simulation | PDF",1789871862,13]