Route optimization for cold chain logistics of front warehouses based on traffic congestion and carbon emission

Abstract

Low-carbon economy is the new tendency of economy development, which is an emerging pathway toward sustainable development of cold chain logistics. This paper studies the cold chain logistics of front warehouses, and a time-depend green vehicle routing problem (TDGVRP) is proposed from the perspective of low-carbon economy. By pouring attention into the fixed cost, refrigeration cost, fuel consumption cost, carbon emission cost, the cost of violating the time window and damage cost, a cold chain logistics routing plan is determined for the vehicle from the distribution center to front warehouses. In the meantime, a new idea of calculating refrigeration cost is proposed. Besides, this paper also explores the effect of traffic congestion and carbon tax of the TDGVRP. A traffic congestion index is used to describe the degree of traffic congestion. Moreover, a hybrid simulated annealing and tempering algorithm (HSATA) is proposed to address this model. The computational results demonstrate that the deteriorating traffic condition would increase carbon emission, while the increased carbon tax would reduce carbon emission within a certain range. The proposed HSATA method enormously reduces the cost of enterprises, which supports the decision-making of cold chain logistics in green and sustainable development.