A bi-objective genetic algorithm for intelligent rehabilitation scheduling considering therapy precedence constraints
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The rehabilitation inpatients in hospitals often complain about the service quality due to the long waiting time between the therapeutic processes. To enhance service quality, this study aims to propose an intelligent solution to reduce the waiting time through solving the rehabilitation scheduling problem. In particular, a bi-objective genetic algorithm is developed for rehabilitation scheduling via minimizing the total waiting time and the makespan. The conjunctive therapy concept is employed to preserve the partial precedence constraints between the therapies and thus the present rehabilitation scheduling problem can be formulated as an open shop scheduling problem, in which a special decoding algorithm is designed. We conducted an empirical study based on real data collected in a general hospital for validation. The proposed approach considered both the hospital operational efficiency and the patient centralized service needs. The results have shown that the waiting time of each inpatient can be reduced significantly and thus demonstrated the practical viability of the proposed bi-objective heuristic genetic algorithm.
KeywordsRehabilitation scheduling Service system Bi-objective Genetic algorithm Precedence constraints Hospital management
This research is supported by Ministry of Science and Technology, Taiwan (NSC 102-2221-E-007-057-MY3; MOST103-2218-E-007-023; MOST104-2911-I-007-502), National Natural Science Foundation of China (#71271068), and the Japan Society of Promotion of Science: Grant-in-Aid for Scientific Research under AQ1 Grant 24510219.0001.
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