Joint Design of Conventional Public Transport Network and Mobility on Demand

TL;DR

This paper presents a bilevel optimization approach to redesign conventional public transport networks by integrating Mobility on Demand, leading to operational cost savings while maintaining quality of service.

Contribution

It introduces a novel bilevel optimization framework combining PSO and LNS for joint PT network redesign and MoD fleet routing, which is computationally efficient and scalable.

Findings

Operational cost savings achieved through network redesign.

Reduced PT coverage with maintained QoS.

Effective solution method tested on large-scale data.

Abstract

Conventional Public Transport (PT) is based on fixed lines, running with routes and schedules determined a-priori. In low-demand areas, conventional PT is inefficient. Therein, Mobility on Demand (MoD) could serve users more efficiently and with an improved quality of service (QoS). The idea of integrating MoD into PT is therefore abundantly discussed by researchers and practitioners, mainly in the form of adding MoD on top of PT. Efficiency can be instead gained if also conventional PT lines are redesigned after integrating MoD in the first or last mile. In this paper we focus on this re-design problem. We devise a bilevel optimization problem where, given a certain initial design, the upper level determines stop selection and frequency settings, while the lower level routes a fleet of MoD vehicles. We propose a solution method based on Particle Swarm Optimization (PSO) for the upper level, while we adopt Large Neighborhood Search (LNS) in the lower level. Our solution method is computationally efficient and we test it in simulations with up to 10k travel requests. Results show important operational cost savings obtained via appropriately reducing the conventional PT coverage after integrating MoD, while preserving QoS.