Optimization of Patient Guidance Path Based on Improved Genetic Algorithm

For the first visit patients, the complexity of diagnosis and treatment spatial environment reduces the accessibility of to the diagnosis room, which causing congestion in hospital. Relying on spatial information to provide patients with a guidance path to the diagnosis room is of practical significance to alleviate the path congestion and reduce the treatment time. Based on spatial grid information, this paper presents an optimization method of guidance path to help find the optimal path. On the basis of generating the initial path with random selection model of path, this method takes the impact of hospital congestion into the optimization objective function, and carries out modeling and optimization combined with the improved genetic algorithm, which is mainly improved in the aspect of crossover that solves the crossover failure due to different path lengths. In the outpatient application of a large hospital, the optimal path is obtained, which proves the effectiveness of the new model.