Optimization of a Low-Carbon Two-Echelon Heterogeneous-Fleet Vehicle Routing for Cold Chain Logistics under Mixed Time Window

Peihan Wen,Ziqi Wang

doi:10.3390/su12051967

Abstract

Due to the rise of social and environmental concerns on global climate change, developing the low-carbon economy is a necessary strategic step to respond to greenhouse effect and incorporate sustainability. As such, there is a new trend for the cold chain industry to establish the low-carbon vehicle routing optimization model which takes costs and carbon emissions as the measurements of performance. This paper studies a low-carbon vehicle routing problem (LC-VRP) derived from a real cold chain logistics network with several practical constraints, which also takes customer satisfaction into account. A low-carbon two-echelon heterogeneous-fleet vehicle routing problem (LC-2EHVRP) model for cold chain third-party logistics servers (3PL) with mixed time window under a carbon trading policy is constructed in this paper and aims at minimizing costs, carbon emissions and maximizing total customer satisfaction simultaneously. To find the optimal solution of such a nondeterministic polynomial (NP) hard problem, we proposed an adaptive genetic algorithm (AGA) approach validated by a numerical benchmark test. Furthermore, a real cold chain case study is presented to demonstrate the influence of the mixed time window’s changing which affect customers’ final satisfaction and the carbon trading settings on LC-2EHVRP model. Experiment of LC-2EHVRP model without customer satisfaction consideration is also designed as a control group. Results show that customer satisfaction is a critical influencer for companies to plan multi-echelon vehicle routing strategy, and current modest carbon price and trading quota settings in China have only a minimal effect on emissions’ control. Several managerial suggestions are given to cold chain logistics enterprises, governments, and even consumers to help improve the development of cold chain logistics.

Highlights

Along with the increasing development of people’s living standards and the adjustment of health concept, the pursuit of fresh and perishable food has become a new normal and created a huge market for the cold chain industry
The main goal of this paper is to develop a LC-2EHVRP model with mixed time window, simultaneously considering economic cost, environmental issue and customer satisfaction for 3PL in cold chain logistics and obtain an optimal solution to deal with it
This paper tackled the low-carbon vehicle routing problem (VRP) for a two-echelon cold chain logistics network which comprised of depots, satellites and customers

Summary

Introduction

Along with the increasing development of people’s living standards and the adjustment of health concept, the pursuit of fresh and perishable food has become a new normal and created a huge market for the cold chain industry. The negative external impacts of freight transportation such as carbon emissions are deserving of attention [2] Since both transporting and keeping the products at given temperatures are energy-intensive processes and generate lots of greenhouse gases (GHG) which are responsible for global climate change, there is a new trend and focus to establish a LC-VRP model of cold chain logistics to reduce CO2 and other GHG emissions through optimizing vehicle routes [3]. A flow of milk supply chain could even contain nine stages from cows to consumers associated with a single milk-processing facility [4]. Under such circumstances, investigating multi-echelon VRP for cold chain is necessary

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Discussion

Conclusion