Abstract：In order to effectively alleviate the problem of parking chaos and difficult parking during massive parking, this paper builds a convex optimization model that takes into account the interests of multiple parties, focusing on parking costs, queuing time and balancing the parking demand among multiple parking lots. First, a stable bilateral matching that minimizes parking fees is derived by using a matching game; then, the research is extended considering the interests of multiple parties at the same time, and the mathematical model constructed is a convex optimization problem, which is solved by the alternating direction multiplier method (ADMM) distributed solution. Finally, the simulation results show that the distributed optimization model based on ADMM can meet the interests of multiple parties compared with the matching game algorithm and the greedy algorithm. It is verified that the ADMM distributed optimization model is more efficient than the centralized optimization model from the aspects of privacy protection, computing time and data transfer volume. It is suitable for massive shared parking matching, and the necessity of considering the interests of multiple parties and the influence of weight coefficients on the calculation results are analyzed and verified.
王震邦, 宋运忠. 考虑多方利益的大规模共享停车匹配优化策略[J]. 复杂系统与复杂性科学, 2023, 20(2): 52-59.
WANG Zhenbang, SONG Yunzhong. A Massive Shared Parking Matching Optimization Strategy Considering the Interests of Multiple Parties. Complex Systems and Complexity Science, 2023, 20(2): 52-59.
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