Multiagent Based Scheduling of Elective Surgery
Author(s)
Khanna, Sankalp
Cleaver, Timothy
Sattar, Abdul
Hansen, David
Stantic, Bela
Year published
2012
Metadata
Show full item recordAbstract
Scheduling of patients, staff, and resources for elective surgery in an under-resourced and overburdened public health system represents an inherently distributed class of problems. The complexity and dynamics of interacting factors demand a flexible, reactive and timely solution, in order to achieve a high level of utilization. In this paper, we present an Automated Scheduler for Elective Surgery (ASES) wherein we model the problem using the multiagent systems paradigm. ASES is designed to reflect and complement the existing manual methods of elective surgery scheduling, while offering efficient mechanisms for negotiation ...
View more >Scheduling of patients, staff, and resources for elective surgery in an under-resourced and overburdened public health system represents an inherently distributed class of problems. The complexity and dynamics of interacting factors demand a flexible, reactive and timely solution, in order to achieve a high level of utilization. In this paper, we present an Automated Scheduler for Elective Surgery (ASES) wherein we model the problem using the multiagent systems paradigm. ASES is designed to reflect and complement the existing manual methods of elective surgery scheduling, while offering efficient mechanisms for negotiation and optimization. Inter-agent negotiation in ASES is powered by a distributed constraint optimization algorithm. This strategy provides hospital departments with control over their individual schedules while ensuring conflict free optimal scheduling. We evaluate ASES to demonstrate the feasibility of our approach and demonstrate the effect of fluctuation in staffing levels on theatre utilization. We also discuss ongoing development of the system, mapping key challenges in the journey towards deployment.
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View more >Scheduling of patients, staff, and resources for elective surgery in an under-resourced and overburdened public health system represents an inherently distributed class of problems. The complexity and dynamics of interacting factors demand a flexible, reactive and timely solution, in order to achieve a high level of utilization. In this paper, we present an Automated Scheduler for Elective Surgery (ASES) wherein we model the problem using the multiagent systems paradigm. ASES is designed to reflect and complement the existing manual methods of elective surgery scheduling, while offering efficient mechanisms for negotiation and optimization. Inter-agent negotiation in ASES is powered by a distributed constraint optimization algorithm. This strategy provides hospital departments with control over their individual schedules while ensuring conflict free optimal scheduling. We evaluate ASES to demonstrate the feasibility of our approach and demonstrate the effect of fluctuation in staffing levels on theatre utilization. We also discuss ongoing development of the system, mapping key challenges in the journey towards deployment.
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Journal Title
Lecture Notes In Computer Science
Volume
7057
Subject
Artificial intelligence not elsewhere classified
Information and computing sciences