The aim of the bi-objective multimodal car-sharing problem (BiO-MMCP) is to determine the optimal mode of transport assignment for trips and to schedule the routes of available cars and users whilst minimizing cost and maximizing user satisfaction. We investigate the BiO-MMCP from a user-centred point of view. As user satisfaction is a crucial aspect in shared mobility systems, we consider user preferences in a second objective. Users may choose and rank their preferred modes of transport for different times of the day. In this way we account for, e.g., different traffic conditions throughout the planning horizon. We study different variants of the problem. In the base problem, the sequence of tasks a user has to fulfill is fixed in advance and travel times as well as preferences are constant over the planning horizon. In variant 2, time-dependent travel times and preferences are introduced. In variant 3, we examine the challenges when allowing additional routing decisions. Variant 4 integrates variants 2 and 3. For this last variant, we develop a branch-and-cut algorithm which is embedded in two bi-objective frameworks, namely the $\epsilon$-constraint method and a weighting binary search method. Computational experiments show that the branch-and cut algorithm outperforms the MIP formulation and we discuss changing solutions along the Pareto frontier.

翻译：双目标多式联运汽车共享问题(BiO-MMCP)的目的是确定旅行的最佳交通分配方式,安排现有汽车和用户的路线,同时尽量减少成本和最大限度地提高用户满意度。我们从以用户为中心的角度调查BiO-MCP。由于用户满意度是共享流动系统的一个关键方面,我们考虑用户偏好第二个目标。用户可以在不同的时间选择和排列他们喜欢的运输方式。我们这样计算整个规划地平线上不同的交通条件。我们研究问题的不同变式。在基本问题上,用户必须完成的任务顺序是事先固定的,旅行时间和偏好是固定的。在规划地平线上,变式2,视时间而定的旅行时间和偏好。在变式3中,我们研究了在允许其他路线决定时遇到的挑战。变式4结合了变式2和变式3。关于最后一个变式,我们开发了一种分行算法,它包含两个双目标框架,即 $\eplon-constraint-comstrain rolational complain-tragational rodument rodumental-bal-bal-tragraphalmogration-tragration-slation-smagraphal-bal rogration-bal-smagraducal rographismogration-shipal romogration-strismasmaxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxgation)。