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Article type: Research Article
Authors: Chen, Ping-Shuna | Tsai, Chia-Chea | Dang, Jr-Fongb; c | Huang, Wen-Tsod; e; *
Affiliations: [a] Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan, Taiwan | [b] Department of Industrial Engineering and Systems Management, Feng Chia University, Seatwen, Taichung, Taiwan | [c] Undergraduate Program of Intellectual Creativity Engineering, National Chung Hsing University, Taichung, Taiwan | [d] Business School, Minnan Normal University, Zhangzhou, Fujian, China | [e] Department of Business Administration, Chung Yuan Christian University, Taoyuan, Taiwan
Correspondence: [*] Corresponding author: Wen-Tso Huang, Department of Business Administration, Chung Yuan Christian University, 200 Chung Pei Road, Chung Li District, Taoyuan 320314, Taiwan. Tel.: +886 32655155; Fax: +886 32655199; E-mail: [email protected].
Abstract: BACKGROUND: This research studies a medical staff scheduling problem, which includes government regulations and hospital regulations (hard constraints) and the medical staff’s preferences (soft constraints). OBJECTIVE: The objective function is to minimize the violations (or dissatisfaction) of medical staff’s preferences. METHODS: This study develops three variants of the three-phase modified bat algorithms (BAs), named BA1, BA2, and BA3, in order to satisfy the hard constraints, minimize the dissatisfaction of the medical staff and balance the workload of the medical staff. To ensure workload balance, this study balances the workload among medical staff without increasing the objective function values. RESULTS: Based on the numerical results, the BA3 outperforms the BA1, BA2, and particle swarm optimization (PSO). The robustness of the BA1, BA2, and BA3 is verified. Finally, conclusions are drawn, and directions for future research are highlighted. CONCLUSIONS: The framework of this research can be used as a reference for other hospitals seeking to determine their future medical staff schedule.
Keywords: Bat algorithm (BA), medical staff scheduling, nurse scheduling/rostering, medical staff’s preferences, workload balance
DOI: 10.3233/THC-202547
Journal: Technology and Health Care, vol. 30, no. 3, pp. 519-540, 2022
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