Patient assignment optimization in cloud healthcare systems: a distributed genetic algorithm

Author:

Pang Xinyu,Ge Yong-FengORCID,Wang Kate,Traina Agma J. M.,Wang Hua

Abstract

AbstractIntegrating Internet technologies with traditional healthcare systems has enabled the emergence of cloud healthcare systems. These systems aim to optimize the balance between online diagnosis and offline treatment to effectively reduce patients’ waiting times and improve the utilization of idle medical resources. In this paper, a distributed genetic algorithm (DGA) is proposed as a means to optimize the balance of patient assignment (PA) in cloud healthcare systems. The proposed DGA utilizes individuals as solutions for the PA optimization problem and generates better solutions through the execution of crossover, mutation, and selection operators. Besides, the distributed framework in the DGA is proposed to improve its population diversity and scalability. Experimental results demonstrate the effectiveness of the proposed DGA in optimizing the PA problem within the cloud healthcare systems.

Funder

Victoria University

Publisher

Springer Science and Business Media LLC

Subject

General Medicine

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