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MATHEMATICAL ANALYSIS OF VEHICLE DELIVERY SCALE OF BIKE-SHARING RENTAL NODES

机译:共享自行车租赁节点的车辆交付规模的数学分析

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Aiming at the lack of scientific and reasonable judgment of vehicles delivery scale and insufficient optimization of scheduling decision, based on features of the bike-sharing usage, this paper analyses the applicability of the discrete time and state of the Markov chain, and proves its properties to be irreducible, aperiodic and positive recurrent. Based on above analysis, the paper has reached to the conclusion that limit state (steady state) probability of the bike-sharing Markov chain only exists and is independent of the initial probability distribution. Then this paper analyses the difficulty of the transition probability matrix parameter statistics and the linear equations group solution in the traditional solving algorithm of the bike-sharing Markov chain. In order to improve the feasibility, this paper proposes a "virtual two-node vehicle scale solution" algorithm which considered the all the nodes beside the node to be solved as a virtual node, offered the transition probability matrix, steady state linear equations group and the computational methods related to the steady state scale, steady state arrival time and scheduling decision of the node to be solved. Finally, the paper evaluates the rationality and accuracy of the steady state probability of the proposed algorithm by comparing with the traditional algorithm. By solving the steady state scale of the nodes one by one, the proposed algorithm is proved to have strong feasibility because it lowers the level of computational difficulty and reduces the number of statistic, which will help the bike-sharing companies to optimize the scale and scheduling of nodes.
机译:针对缺乏科学合理的车辆交付规模判断和调度决策优化不足的问题,基于自行车共享使用特点,分析了马尔可夫链离散时间和状态的适用性,并证明了其性质。不可减少,非周期性和正向复发。基于以上分析,本文得出结论:共享单车马尔可夫链的极限状态(稳态)概率仅存在,并且与初始概率分布无关。然后,分析了传统的共享自行车马尔可夫链求解算法中过渡概率矩阵参数统计和线性方程组求解的难点。为了提高可行性,本文提出了一种“虚拟两节点汽车尺度解决方案”算法,该算法将要求解的节点旁边的所有节点都视为一个虚拟节点,提供了转移概率矩阵,稳态线性方程组和与稳态尺度,稳态到达时间和待求解节点的调度决策有关的计算方法。最后,通过与传统算法的比较,评估了该算法稳态概率的合理性和准确性。通过逐一求解节点的稳态尺度,证明了该算法具有较强的可行性,因为它降低了计算难度,减少了统计量,这将有助于共享单车的公司优化尺度和规模。节点调度。

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