Finding the trade-off between gas emissions and disturbance in an urban context

We introduce the bi-objective emissions disturbance traveling salesman problem (BEDTSP), which aims at minimizing carbon dioxide emissions (CO2) as well as disturbance to urban neighborhoods, when planning the tour of a single vehicle delivering goods to customers. Although there exist recent studies on minimizing emissions, we are not aware of any work on minimizing disturbance. We develop four different mathematical models for the BEDTSP. We also develop several data generation strategies for minimizing disturbance. These strategies consider optional nodes, thus allowing detours that yield less disturbance but also possibly more emissions. All models and strategies are compared in an extensive computational study. Experimental results allow us to derive clear guidelines for which model and data generation strategy to use in which context. Following these guidelines, we conduct a case study for the city of Vienna.