ObjectiveTo propose an effective algorithm for solving the shortest circuit problem of military health support.MethodsPartheno-genetic algorithm (PGA),which only used mutation operation and selection operation,was adopted in the present study.The algorithm was based on K-random-nearer-neighbor algorithm combined with two-random-point exchange,two-neighbor-point exchange,circular-based part inversion and random insertion mutation operations.Furthermore,greedy strategy was applied in selection to improve the hill-climbing capability of PGA.ResultsThe simulation results of CTSP31 and standard dataset from TSP library indicated that the PGA was more effective than existing algorithms from the literature.ConclusionPGA can serve as a basis for further development of a computer-assisted program,and it provides optimized decision-making scheme for improving the quality and speed of military medical service disposition.