Research on VRP Model Optimization of Cold Chain Logistics Under Low-Carbon Constraints

Introduction

In recent years, cold chain logistics has developed rapidly. As a representative industry for consumption upgrades in the logistics industry, it has received extensive attention (L. Zhang et al., 2019). China's aquatic product market, meat product market, agricultural product market, quick-frozen food market, and dairy product market all have broad development prospects. According to statistics, in 2017, the total demand for cold chain logistics in China reached 147.5 million tons, an increase of 22.5 million tons over the previous year. The total value of currency in circulation reached four trillion yuan, an increase of 18% year-on-year. The total revenue of the logistics industry was 255 billion yuan, a year-on-year increase of 13.3% (Y. Zhang et al., 2020).

The low-carbon concept advocated by the Chinese government continues to deepen, and cold-chain logistics distribution companies are gradually integrating low-carbon in the distribution process, comprehensively considering economic and environmental benefits (Chaudhuri et al., 2018). In the field of cold chain distribution, some experts and scholars have put forward corresponding suggestions for the low carbon emission of cold chain logistics (Rahmani et al., 2018). In order to enable cold chain distribution companies to achieve the goal of energy saving and emission reduction (Li et al., 2022), many scholars take carbon emission factors into consideration when studying the path optimization problem of a single distribution center and the path optimization problem of multiple distribution centers (Behzadi et al., 2013).

Taking into account the insufficient capacity of a single distribution center, scholars have gradually shifted from the study of single distribution center path optimization to multi-distribution center path optimization, taking carbon emission factors into consideration (Azad et al., 2022). However, this kind of research is relatively rare (Tan et al., 2006). Based on the concept of green logistics development (Kainuma & Tawara, 2006), some scholars have cost carbon emissions and proposed a cold chain distribution path optimization problem in which enterprises have multiple distribution centers (Gunasekaran & Ngai, 2012). Some scholars have proposed a multi-park green vehicle routing problem (Rabbani et al., 2018), constructed a multi-objective mathematical model that maximizes revenue (Lai et al., 2004), minimizes cost, minimizes time, and minimizes emissions and uses an improved ant colony optimization algorithm to effectively solve it (Jayaram & Tan, 2010). Some scholars have studied the multi-park vehicle routing problem with time windows (Chen, 2021). Under the constraints of time windows, vehicle capacity, fleet size, etc., they have constructed a multi-objective mathematical model with minimum total cost, fuel consumption, and carbon dioxide emissions as the optimization goals (W. Wang et al., 2021). A meta-heuristic algorithm based on ant colony algorithm is proposed to solve the problem (Ren et al., 2020).