Measurement, evaluation and minimization of CO2, NOx, and CO emissions in the open time dependent vehicle routing problem

Abstract

In this paper, a new comprehensive model has been presented for the measurement, evaluation and minimization of CO2, NOx and CO as three important emissions (emitted from vehicles) in the open time dependent vehicle routing problem (OTDVRP). In the OTDVRP, traffic properties of congested regions like city centers are considered. Travel time between two points depends on the time of departure, and the vehicles do not come back to the depot. In some distribution companies, vehicles are rental; therefore, they do not come back to the depot from the last customer. To solve the proposed problem, an improved Particle Swarm Optimization algorithm is developed. The results show good performance in computation experiments compared to original PSO algorithm. The results of the experiments show that considering minimization, the pollutants can reduce emissions by 16% on the average compared to the classical open TDVRP. Factors causing the variation in emissions are also identified and discussed in this study.