Waiting Time Management, Its Consideration with Business Analytics, and Operating Autonomous Vehicles

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My research team has made substantial progress over the last 5 years. This proposal examines (I) queueing theory and waiting time management, (II) waiting time management with analytics in healthcare, and (III) the impact of Autonomous Vehicles (AVs) on welfare. I. Queueing Theory and Waiting Time Management We developed the Queueing and Markov Chain Decomposition (QMCD) methodology that international queueing theorists currently use. To further disseminate QMCD, we will characterize the problems it can solve, such as multi-servers queues. We will study such queues in the presence of priority and abandonments. These, well-known, open, problems are also appropriate for traffic intersections and will support project III. We will continue to study queueing location models that are critical for firms' expansions. The failure of Target in Canada demonstrates the consequence of poor expansion planning. We will study healthcare related phenomena in queues in the presence of triage and service level targets (see, e.g., Canadian Triage and Acuity Scale) to support project II. II. Waiting Time Management with Analytics in Healthcare A critical healthcare issue is the management of waiting in Emergency Departments (EDs) and for elective surgeries. For example, the wait for 10% of adult surgeries in BC is more than 31 weeks, see https://swt.hlth.gov.bc.ca/faces/Wooden.xhtml. We will use data to establish effective management of EDs, calculate the imputed healthcare effects of wait time reduction in EDs, help EDs to improve their processes, and devise effective algorithms to schedule surgeries while considering downstream medical and surgical beds. III. The Impact of Autonomous Vehicles (AVs) on Quality of Life AVs may soon compose the backbone of land transportation, yet little research on AVs' impact on welfare is available to support policies on their deployment. We will study how AVs can be effectively share, consider sizes of AVs and lane allocation, analyze the safety and healthcare implications of AVs (annually, nearly 1.3 million people are killed in accidents, see http://asirt.org/initiatives/informing-road-users/road-safety-facts/road-crash-statistics), consider taxation of electric AVs in the replacement of gas tax to support infrastructure, and examine how to coordinate AVs. Contributions: The proposed research program will: train highly qualified personnel, improve the control of important applications, and develop new theories. Specifically, (I) will lead to a breakthrough in queueing theory via the assimilation of the QMCD methodology we developed, (II) will improve the healthcare delivery process and its results for emergency and pre-surgery patients, and (III) will provide, science based, guidelines for Canadian policy makers on the deployment of AVs.