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Wei Xiang

Wei Xiang

Ningbo University, China

Title: An Intelligent Operating Rooms Scheduling under Mass Causalty Events

Biography

Wei Xiang has obtained her PhD from Nanyang Technological University in Singapore. She is currently the Vice-Dean of Department of Industry Engineering
in Ningbo University, China. Her research interests cover manufacturing system engineering, operational research, planning and scheduling in healthcare
management and swarm intelligence application in healthcare. She has published around 30 papers in various journals

Abstract

Mass casualty events generate large numbers of acutely ill or injured people who require immediate medical health care.
Th e Operating Room (OR) is the key department that provides surgeries to victims. Effi cient management and allocation
of scarce medical resources in ORs can improve outcomes for victims of mass casualty events, operating rooms scheduling
deals with determining surgeries sequence and allocating medical resources. Under mass casualty event, operating rooms
scheduling calls for a dynamic scheduling with a wide variety of patients, surgeries and unforeseen emergencies. Dynamic
scheduling does not create or update schedules; instead, the scheduling mechanism is based on decentralized dispatching. Th e
research interest here focuses on an agent-based approach to scheduling of dynamic operating rooms. Th e operating rooms can
be built up by heterogeneous intelligent agents involving patients, surgeries, medical resources, staff s like doctors, nurses and
anesthetists with diverse goals, constraints and behaviors. Th ese agents have emergent behavior in response to disturbances
in the environment and generate fl exible scheduling in a dynamically adaptive way. In order for a multi-agent-system to
solve such distributed operating rooms scheduling problem coherently, agents must communicate amongst themselves and
coordinate their activities to make decisions. Ant colony intelligence is proposed to be combined with local agent coordination
so as to make autonomous agents adaptive to changing circumstances and to give rise to effi cient global performance under
mass casualty events..