EURO 2024 Copenhagen
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3153. Unleashing Mixed Integer Linear Programming: Optimal Shuttle Routing Solutions for Enhanced Urban Mobility

Invited abstract in session WA-55: MOST - MaaS & Innovative Services for Sustainable Mobility, stream Transportation.

Wednesday, 8:30-10:00
Room: S02 (building: 101)

Authors (first author is the speaker)

1. Marco Fabris
Department of Information Engineering, University of Padova

Abstract

Efficient urban mobility is paramount in the evolving landscape of Mobility as a Service (MaaS). This study tackles a shuttle routing problem within this framework, akin to the orienteering problem, aimed at optimizing existing transportation networks. The problem involves optimizing shuttle routes through a directed graph representing an urban network, where nodes correspond to shuttle stops and edges depict road connections with associated travel times. Users at stops need to reach a common destination under specific time constraints, including arrival time and a tolerance window. The primary objective is to maximize passenger count while adhering to these constraints and operating within a predefined service time window. A mixed integer linear program (MILP) has been developed to obtain exact optimal solutions, so far demonstrating efficacy for networks of up to 15 nodes within reasonable computational time. The MILP discretizes shuttle time resources, thus ensuring solutions to be characterized by loop-free paths and optimal time schedules for the picked-up users. Further refinements to this result consider practical limitations, such as the shuttle capacity, and fairness-based incentives for people in order to strategically foster this kind of mobility (e.g., by favoring remote nodes). This approach lays the groundwork for scalable solutions in terms of both urban networks and number of deployed shuttles, as well as for real-time data integration for dynamic scheduling.

Keywords

Status: accepted

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