| Summary: | 碩士 === 國防大學理工學院 === 兵器系統工程碩士班 === 97 === The travel time of a vehicle is varied with traffic conditions such as traffic jam, accidents or climate situations. To simulate these traffic conditions of road network, this thesis aims at active transportation in military to construct a vehicle routing model with random travel time. Furthermore, a hybrid particle swam optimization (HPSO) is proposed to optimize the constructed model and thus determine the routing path of the active transportation in military. The contributions of this thesis are expected to be capable of utilizing the limited logistics resources efficiently by shrinking routing length, reducing required number of vehicles, and improving loading rate of vehicles to enhance the logistics capacity. The proposed HPSO is on the basis of improving a developed discrete PSO at which the sweep method and nearest addition method are adopted to generate the excellent initial PSO population. Moreover, the response surface methodology (RSM) derived from designs of experiments is employed to determine the optimal settings of HPSO search parameters. The international CVRP benchmark problems are applied to verify the effectiveness of the proposed HPSO. Finally the proposed approach is employed to solve an actual military problem in active transportation.
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