A Distributed Optimized Patient Scheduling using Partial Information
This addresses scheduling inefficiencies in hospitals, though it appears incremental as it builds on existing multi-agent system approaches.
The paper tackles the problem of dynamic patient scheduling in hospitals by proposing DOPSG, a distributed method that uses partial information to schedule patients across multiple departments, reducing waiting times and resource idle times.
A software agent may be a member of a Multi-Agent System (MAS) which is collectively performing a range of complex and intelligent tasks. In the hospital, scheduling decisions are finding difficult to schedule because of the dynamic changes and distribution. In order to face this problem with dynamic changes in the hospital, a new method, Distributed Optimized Patient Scheduling with Grouping (DOPSG) has been proposed. The goal of this method is that there is no necessity for knowing patient agents information globally. With minimal information this method works effectively. Scheduling problem can be solved for multiple departments in the hospital. Patient agents have been scheduled to the resource agent based on the patient priority to reduce the waiting time of patient agent and to reduce idle time of resources.