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Planning Shared Corporate Mobility Services
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DOI：10.1016/j.trpro.2017.12.141.png)
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Abstract
En 中文
In a corporate context, individual mobility of employees is often addressed by owning cars instead of using mobility at least in Austria. Therefore, the national research project SEAMLESS Sustainable, Efficient Austrian Mobility with Low-Emission Shared Systems aims at providing novel company mobility services considering private and business trips. The idea is to shift from owning overdimensioned and underutilized cars towards using sustainable and flexible mobility offers including car pools, bike sharing, taxis, and/or public transportation services. The goal is to achieve a more efficient utilization and possibly a reduction of the company fleet as well as a significant CO2 reduction by fostering the usage of the aforementioned alternatives. In order to achieve this, not only business culture and employees' perception have to be investigated but also a thorough technical support must be provided. Within the model presented in this work, we focus on fulfilling the original mobility demand by incorporating alternative mobility modes such as shared (e-)cars and bikes, or public transport. At the same time, side constraints related to e mobility (e.g., temporal load distribution to avoid peaks on the energy grids) are considered. The resulting models aim at combining different well-known and so-far mostly individually considered problems like electric vehicle routing with time windows, fleet size and mix, vehicle-to-tour assignment, battery load management, and general fleet management operations. In this work, we will report on first mixed integer linear optimization models focusing on multimodal mobility and fleet management. (C) 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 20th EURO Working Group on Transportation Meeting.
Keywords:
corporate mobility
shared mobility
multimodal transportation
mixed integer linear programming
combinatorial optimization
integrated problem modelling
fleet size and mix
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