A Novel 3D Approach for Patient Schedule Using Multi-Agent Coordination

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Author(s): E. Grace Mary Kanaga (Karunya University, India), M.L. Valarmathi (Government College of Technology, India)and Preethi S.H. Darius (Karunya University, India)
Copyright: 2012
Pages: 20
Source title: Cross-Disciplinary Applications of Artificial Intelligence and Pattern Recognition: Advancing Technologies
Source Author(s)/Editor(s): Vijay Kumar Mago (Simon Fraser University, Canada)and Nitin Bhatia (DAV College, India)
DOI: 10.4018/978-1-61350-429-1.ch027

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

This chapter presents a novel 3D approach for patient scheduling (3D-PS) using multi-agents. Here the 3Ds refers to the Distributed, Dynamic and Decentralized nature of the patient scheduling. As in many other scheduling problems, in the hospital domain, a major problem is the efficient allocation of resources to the patients. The resources here mean the doctor, diagnosing equipments, lab tests, et cetera. Commonly, patient scheduling is performed manually by human schedulers with no automated support. Human scheduling is not efficient, because the nature of the problem is very complex; it is inherently distributed, dynamic, and decentralized. Since agents are known to represent distributed environment well and also being capable of handling dynamism, an agent based approach is chosen. The objectives are to reduce patient waiting times, minimize the patient stay in the hospital, and to improve resource utilization in hospitals. The comparison of several agent-based approaches is also reviewed, and the auction-based approach is chosen. The complete multi-agent framework given in literature is adapted to suit the patient scheduling scenario. The patient scheduling system is implemented in the JADE platform where patients and resources are represented as agents. The chief performance metric is the weighted tardiness which has to be minimized in order to obtain an effective schedule. The experiment is carried out using constant number of resources and varying number of patients. The simulation results are presented and analyzed. 3D-PS produces up to 30% reduction in total weighted tardiness in a distributed environment, as compared to other traditional algorithms. A further enhancement to this approach aims to reduce the communication overhead by reducing the number of messages passed and hence resulting in a better coordination mechanism. This auction based mechanism aims to provide the basic framework for future enhancements on patient scheduling.

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