A novel genetic algorithm based system for the scheduling of medical treatments

Squires, Matthew and Tao, Xiaohui ORCID: https://orcid.org/0000-0002-0020-077X and Elangovan, Soman and Gururajan, Raj ORCID: https://orcid.org/0000-0002-5919-0174 and Zhou, Xujuan and Acharya, Udyavara Rajendra (2022) A novel genetic algorithm based system for the scheduling of medical treatments. Expert Systems With Applications, 195:116464. pp. 1-12. ISSN 0957-4174


The manual scheduling of medical treatment in a health centre is a complex, time consuming, and error prone task. Furthermore, there is no guarantee a manually generated schedule maximises the operational efficiency of the centre. Scheduling problems have seen extensive research across several domains. The current work presents a novel genetic algorithm for the scheduling of repetitive Transcranial Magnetic Stimulation (rTMS) appointments. The proposed List Scheduling Wildcard Tournament Genetic Algorithm (LSWT-GA) combines an innovative survivor selection policy with heuristic population initialisation. The algorithm aims to optimise the operational efficiency of a medical centre through efficient rTMS appointment scheduling. Additionally, the algorithm has the capacity to consider patient priority. Empirical experiments were conducted to evaluate the performance of the proposed algorithm, using a synthetic data set specifically developed to simulate the medical treatment scheduling problem. The experimental results showed the LSWT-GA algorithm outperforms other algorithms, obtaining the optimal makespan more frequently than a List Scheduling Genetic Algorithm (LS-GA) using traditional survivor selection policies and a standard genetic algorithm using random population initialisation (Random-GA). In addition to the novel genetic algorithm, LSWT-GA, the paper also makes a theoretical contribution by evaluating the run time of the LSWT-GA for makespan minimisation. The proposed algorithm and related findings can be applied directly to the administration systems in medical and healthcare centres and helps improve the deployment of medical resources for better treatment effect.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty/School / Institute/Centre: Current – Faculty of Health, Engineering and Sciences - School of Mathematics, Physics and Computing (1 Jan 2022 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Date Deposited: 09 Mar 2022 05:08
Last Modified: 23 Sep 2022 02:06
Uncontrolled Keywords: Genetic Algorithm; List Scheduling Wildcard Tournament Genetic Algorithm (LSWT-GA); Medical scheduling; repetitive Transcranial Magnetic Stimulation (rTMS)
Fields of Research (2008): 08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080105 Expert Systems
08 Information and Computing Sciences > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining
11 Medical and Health Sciences > 1103 Clinical Sciences > 110319 Psychiatry (incl. Psychotherapy)
08 Information and Computing Sciences > 0807 Library and Information Studies > 080702 Health Informatics
Fields of Research (2020): 42 HEALTH SCIENCES > 4203 Health services and systems > 420308 Health informatics and information systems
46 INFORMATION AND COMPUTING SCIENCES > 4609 Information systems > 460902 Decision support and group support systems
46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460209 Planning and decision making
Socio-Economic Objectives (2008): C Society > 92 Health > 9202 Health and Support Services > 920209 Mental Health Services
B Economic Development > 89 Information and Communication Services > 8903 Information Services > 890301 Electronic Information Storage and Retrieval Services
E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Socio-Economic Objectives (2020): 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences
22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220403 Artificial intelligence
Identification Number or DOI: https://doi.org/10.1016/j.eswa.2021.116464
URI: http://eprints.usq.edu.au/id/eprint/46996

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