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Clinical exercises are necessary components of the national license for clinical engineering. Clinical exercise scheduling in a training institution is regarded as example of a optimization problem. Furthermore, it is well-known that finding the optimal solution for an optimization problem is difficult. In fact, it is also well-known that metaheuristics can produce approximate solutions given sufficient quality. In this paper, we thus propose a scheduling method for clinical exercises using tabu search, which is a type of metaheuristics. The problem is to assign trainees to hospitals so that they can take a suitable variety of clinical exercises. Hospitals provide different clinical exercises with different schedules. From the problem, we first derived 9 constraints for scheduling and then defined an objective function for identifying a solution effectively. The objective function penalizes constraint violations. Our method aims to produce a solution and ignore the difference among possible solutions. We designed an application that creates schedules by implementing the tabu search method. This application takes essential information such as the number of trainee groups, hospitals, and exercises and outputs a schedule file. Results showed the application could output a schedule for 60 students, 4 hospitals, 5 practices and 15 groups in approximately 2 minutes.
Research papers (academic journals)
