Differing from the conventional fixed-route transit, Demand Responsive Connector (DRC) is scheduled to pick up passengers based on requests, and delivers them to a common destination (e.g., a metro station). The demand for DRC is affected by not only the fare and travel time, but also time reliability. The latter’ impact is non-negligible because of the uncertainty nature of DRC on collecting the temporally and spatially distributed passengers. This paper explicitly introduces an elastic demand function embedded with a time deviation penalty model. Based on that, one-vehicle and two-vehicle DRC models are formulated to maximize the social welfare. The decision variables include fare, service area, and operating cycle time. Augmented Lagrange Multiplier Method is applied to solve the optimization problem. Simulation is performed to verify the validity of the models. In numerical studies, sensitivity analysis unveils the influences of several key parameters, e.g., potential demand density, vehicle capacity, line-haul distance and elasticity factors. By comparison, threshold values of demand density are revealed for the applicability of the one-vehicle and two-vehicle schemes. The proposed model provides a decision-making tool for DRC operators considering local conditions.

中文翻译：

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考虑弹性需求的需求响应连接器服务的优化设计

与常规的固定路线运输不同，按需响应连接器（DRC）计划根据请求来接送乘客，并将其交付到公共目的地（例如，地铁站）。对DRC的需求不仅受票价和旅行时间的影响，还受时间可靠性的影响。后者的影响是不可忽略的，因为刚果（金）在收集时空分布的乘客方面具有不确定性。本文明确介绍了嵌入有时间偏差惩罚模型的弹性需求函数。在此基础上，建立了单车和两车的DRC模型，以最大程度地提高社会福利。决策变量包括票价，服务区域和运营周期时间。应用增强拉格朗日乘数法解决了优化问题。进行仿真以验证模型的有效性。在数值研究中，敏感性分析揭示了几个关键参数的影响，例如，潜在需求密度，车辆容量，线路运输距离和弹性系数。通过比较，揭示了需求密度的阈值对于一车和两车方案的适用性。所提出的模型为刚果民主共和国运营商考虑当地条件提供了决策工具。