Vehicle routing problem with time windows considering carbon emission

Abstract

Abstract Logistics and transportation industry is not only a major energy consumer, but also a major carbon emitter. Developing green logistics is the only way for the sustainable development of logistics industry. One of the main factors of environmental pollution is caused by carbon emissions in the process of vehicle transportation, and carbon emissions of vehicle transportation is closely related to routing, time-dependent speed and the slope of road. Therefore, vehicle routing problem with time windows considering carbon emissions is presented in this paper. a mixed integer programming model is built to describe the carbon emission optimization problem under the constraint of time windows. In this programming model, the high-granularity predictive speeds are used to compute carbon emissions. And to solve this problem, a hybrid genetic algorithm with adaptive variable neighborhood search method is presented. A case study with the logistics and traffic data in Jingzhou, China is validated, and the results shows that the effectiveness of the proposed model and algorithm.