论文标题
在不确定性下的汽车共享定价和搬迁问题的确切解决方案
Exact solutions to a carsharing pricing and relocation problem under uncertainty
论文作者
论文摘要
在本文中，我们研究了共同决定汽车共享价格和车辆搬迁的问题。我们考虑在多模式城市运输系统的背景下运行的汽车共享服务。定价决定考虑了替代运输模式的可用性以及客户对这些的偏好。为了说明客户偏好的固有不确定性，该问题被称为一个混合成员两阶段随机程序，在两个阶段都有整数决策变量。我们基于整数L形方法为问题提出了一种精确的解决方案方法，该方法利用了子问题解决方案的有效精确算法。基于米兰市对人工实例的测试表明，该方法可以解决或找到良好的解决方案，以使商业求解器失败的适度大小实例。此外，我们的结果表明，通过调整城市不同区域之间的价格，运营商可以吸引比固定的定价计划更大的需求，并且这种定价计划与足够大的车队相结合，大大降低了基于员工的重新货币的相关性。在我们的结论中指出，在未来的研究中仍有待解决的许多问题。
In this article we study the problem of jointly deciding carsharing prices and vehicle relocations. We consider carsharing services operating in the context of multi-modal urban transportation systems. Pricing decisions take into account the availability of alternative transport modes, and customer preferences with respect to these. In order to account for the inherent uncertainty in customer preferences, the problem is formulated as a mixed-integer two-stage stochastic program with integer decision variables at both stages. We propose an exact solution method for the problem based on the integer L-Shaped method which exploits an efficient exact algorithm for the solution of the subproblems. Tests on artificial instances based on the city of Milan illustrate that the method can solve, or find good solutions to, moderately sized instances for which a commercial solver fails. Furthermore, our results suggest that, by adjusting prices between different zones of the city, the operator can attract significantly more demand than with a fixed pricing scheme and that such a pricing scheme, coupled with a sufficiently large fleet, significantly reduces the relevance of staff-based relocations. A number of issues, that remain to be addressed in future research, are pointed out in our conclusions.
