Electric Transit Route Network Design Problem: Model and Application

Abstract

Electric buses have long been recognized as a promising direction for offering sustainable public transportation services. While range and battery performance constraints have hindered the widespread adoption of electric buses in the past, technological advances make them a prominent and attractive option for public transportation in the future. Still, operational constraints and the need for additional (charging) infrastructure highlight the need for introducing appropriate decision-making tools, tailor-made for supporting the design of transit networks operated by electric buses. This paper focuses on developing and testing a comprehensive route design model for the case of a transit network, operated exclusively by an electric bus fleet (Electric Transit Route Network Design Problem—E-TRNDP). The model is formulated as a bi-level optimization problem, which attempts to jointly design efficient transit routes and locate required charging infrastructure. A multi-objective, particle swarm optimization algorithm, coupled with a mixed linear—integer programming model is used to solve the model. An existing benchmark network is used as a test-bed for the proposed model and solution process; results illustrate that the proposed model and solution method yield realistic design outcomes in an acceptable time frame.

Solar-powered bus route: introducing renewable energy into a university campus transport system

“…Last but not least, it should be noted that the results are highly dependent on the selected capacity factor, which is shown to often deviate from theoretical values, especially in renewable energy technologies (Boccard, 2009;Ioannidis and Koutsoyiannis, 2019).…”

“…els installed in close proximity to the bus stop and transporting the energy to buses via induction (Franken and Meijer, 2014; Kawashima and Fujioka, 2008). This charging configuration is referred to as opportunity charging, as buses charge during dwell times at stops through high-power chargers (Iliopoulou et al, 2019;Lajunen, 2018). In this case, we assume that candidate stop locations must be within the campus, while the stops exposed to the highest amount of solar radiation must be exploited.…”

Optimal route design of electric transit networks considering travel reliability

“…Traffic congestion, energy consumption, and air pollution have been significant issues for large cities. Sustainable transportation modes, especially public transport, are expected to offer attractive alternatives to private cars (Gao et al., 2020; Gao et al., 2021; Iliopoulou, Tassopoulos et al., 2019). Transit network is the “infrastructure” of the bus transit system that determines the efficiency and service level of public transport (Yao et al., 2014).…”

A Particle Swarm Optimization Algorithm for the Solution of the Transit Network Design Problem

“…In the light of these contributions, this study addresses the TNDP and shows an innovative solving procedure, based on a new approach for optimal bus network calculation for real-size cities: the PSO algorithm. To best of our knowledge, the PSO algorithm has been recently tested for the TNDP on benchmark networks [27,28], but experiments on larger networks were left for future works.…”