| Summary: | 博士 === 國立交通大學 === 工業工程與管理系所 === 103 === It has been important to make a fair and satisfactory schedule for nursing staff. In the previous works, the satisfaction of nursing staff for schedule was usually based on the total amount of assignments of the preferred shifts and days-off of the nursing staff at the current planning period. However, the design of such satisfaction has some flaws, as nursing staff have other different preference ranks for shifts and days-off, which may affect fairness of schedule, and numbers of the preferred shifts and days-off are not equivalent so that the planned schedule might be biased. Therefore, this dissertation proposes a novel satisfaction which takes into account the balance of the preference weights for shifts and days-off, different preference ranks towards each shift, the priority ordering of the nursing staff for planning their shift schedule, and the historical data of previous planning period. The proposed satisfaction can fairly satisfy all the nursing staff’s preferences for shifts and days-off to maximize the satisfaction of the nursing staff for their schedules. In addition, the dissertation considered schedule constraints to build a model based upon integer programming to an optimal solution of schedule in small-scale problems, and develops three improved genetic algorithms including improved genetic algorithm (IGA), hybrid genetic algorithm (HGA) and genetic algorithm with immigrant scheme (GAIS), to search near optimal solutions of schedules in large-scale problems. The main contribution of our research is that we consider that the nursing staff’s satisfaction is affected by multiple preference ranks and their priority ordering to be scheduled, so that the quality of the generated schedule is more reasonable.
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