Impact of Congestion Pricing Schemes on Costs and Emissions of Commercial Fleets in Urban Areas

As urbanization increases, municipalities across the world have become aware of the negative impacts of road-based transportation, which include traffic congestion and air pollution. As a result, several cities have introduced tolling schemes to discourage vehicles from entering the inner city. However, little research has been done to examine the impact of tolling schemes on the routing of commercial fleets, especially on the resulting costs and emissions. In this study, we investigate a vehicle routing problem considering different congestion charge schemes for several city types. We design comprehensive computational experiments to investigate whether different types of tolling schemes work in the way municipalities expect and what factors affect the performance of the congestion charge schemes. We compare the impact on a company\u27s tota

Flexible dynamic time window pricing for attended home deliveriesy

In the challenging environment of attended home deliveries, pricing of different delivery options can play a crucial role to ensure profitability and service quality of retailers. To differentiate between standard and premium delivery options, many retailers include time windows of various lengths and fees within their offer sets. Customers want short delivery time windows, but expect low delivery fees. However, longer time windows can help to maintain flexibility and profitability for the retailer. We present flexible dynamic time window pricing policies that measure the impact of short time windows on the underlying route plan during the booking process and set delivery fees accordingly. Our goal is to nudge customers to choose time windows that do not overly restrict the flexibility of route plans. To this end, we introduce three dynamic pricing policies that consider temporal and/or spatial routing and customer characteristics. We consider customer behavior through a nested logit model, which is able to mimic customer choice for time windows of multiple lengths. We perform a computational study considering realistic travel and demand data to investigate the effectiveness of flexible dynamic time window pricing. Our pricing policies are able to outperform static pricing policies that reflect current business practice