关键词: 随机数生成算法, 拉丁超立方抽样, 车牌摇号, 多重采样策略

Abstract: Beijing and other places get car indicators by random shaking way currently. However simple random manner will lead to “shake not” phenomenon, and not consider the rigid demand for vehicles. For the above unfairness, a weighted sampling strategies by groups is presented in this paper：Group model based on shaking time, considering unshaken numbers, eliminate?“shake not” by assigning group rates；Group model based on the number of vehicles, considering the actual needs, focus on some applicants?by assigning the extraction ratio. Combined this two models, this paper proposes vehicle indicators randomly distributed algorithm based on multi-sampling strategy, eliminating the unfairness comprehensively. The simulation results show that the algorithm presented in this article can effectively reduce the unreasonable factors, providing a new way to solve the vehicle?shaking problem.

Key words: random generator, latin hypercube sampling, license rocking, multi-sampling strategy