Nighttime Vehicle Routing for Sustainable Urban Logistics

Abstract

Vehicle routing problems play a critical role in logistics distribution, allowing companies to minimize operational parameters such as cost, fuel consumption, emissions etc. This paper studies a customized vehicle routing problem incorporating nighttime delivery options for a heavily congested urban area. The aim is to identify the optimal combination of day and night routes by trading off between fuel and staff costs. A Linear Programming (LP) formulation for the Night Time Vehicle Routing Problem (NTVRP) is introduced. The model is then applied to a case study using real data from a department store in Bangkok, Thailand. A fuel consumption model is used alongside an emission model to estimate the beneficial impact of NTVRP on both costs and emissions. Results show that when demand is high and 55 tonne heavy goods vehicles are used, the cost savings are about 16.7 percent. More significantly, CO2 emissions are reduced by more than 30 percent. With low demand, cost savings are more than 30.8 percent, together with a 28.2 percent reduction in CO2 emissions. Overall, the case study shows that nighttime delivery is a viable option to increase efficiency and sustainability of a logistics company.