Electric buses (EBs) are considered a more environmentally friendly mode of public transit.
In addition to other practical challenges, including high infrastructure costs and short driving …

The study aims to develop an analytical framework for assessing cycling infrastructure from
adolescents' safety perspectives, facilitating the prioritisation of areas based on …

In this paper, we determine a welfare-optimal investment strategy for bicycle networks while
considering the joint impact of travel time savings and induced demand throughout the …

Planning a public transit network is a challenging optimization problem, but essential in
order to realize the benefits of autonomous buses. We propose a novel algorithm for …

This study introduces an approach for route optimization of many-to-many Demand-
Responsive Transport (DRT) services. In contrast to conventional fixed-route transit systems …

This paper considers the use of deep learning models to enhance optimization algorithms
for transit network design. Transit network design is the problem of determining routes for …

Mobility service route design requires demand information to operate in a service region.
Transit planners and operators can access various data sources including household travel …

In this work we explore the combination of metaheuristics and learned neural network
solvers for combinatorial optimization. We do this in the context of the transit network design …

Transit agencies world-wide face tightening budgets. To maintain quality of service while
cutting costs, efficient transit network design is essential. But planning a network of public …

This paper introduces a bilevel programming model for optimizing transit network departure
frequency. In the upper‐level model, user satisfaction is reflected by considering congestion …