## 1 Introduction  
The sudden outbreak of the novel coronavirus thrust the issue of pharmaceutical cold chain logistics into the spotlight. The pharmaceutical cold chain is a crucial link in drug transport, with tremendous potential for industrial development [1]. Meanwhile, the emergence of \"two votes\" and the new GSP certification specification, accompanied by stricter supervision over procedures such as procurement, storage, and sale, make the direct distribution from pharmaceutical plants to dealers or hospitals seemingly more profitable and feasible. However, many logistics enterprises cannot meet the requirements of the latest pharmaceutical cold chain logistics; as a result, drug distribution tasks are performed independently by pharmaceutical manufacturers. In addition, since the pharmaceutical cold chain logistics is still in its early stage [2], the comprehensive cost and carbon emissions are not ideal. Pertaining to this condition, studies showed that the logistics activities of carrier vehicles, especially those involved in cold chain logistics, are a main factor contributing to global warming (see [3, 4]). Moreover, this goes against the prevalent \"low-carbon environmental protection\" concept, while being unfavorable toward the battle of pollution prevention and control. Therefore, optimizing the pharmaceutical cold chain logistics path and reducing carbon emissions in logistics management became the focus of research [3]. Currently, there are three main research topics for cold chain logistics optimization. The first one is the optimization of cold chain logistics efficiency, which involves improving properties, infrastructure maintenance, and management practices [5]. The second one is the optimization of logistics decision making, such as route optimization and energy optimization [6]. The last one is about environmentally friendly logistics that reduce carbon emissions and energy consumption [7].  
The contributions of this study are as follows:  
1. Proposal of a new medicine cold chain distribution model, which is different from the existing single transport vehicle scheme.
2. Considerations of the influence of spatial and seasonal temperature variations on customers from distinct areas and a further refinement of transportation costs, especially for the issues of consumables in cold zones.
3. Acceleration of the convergence speed, while avoiding local optimal solutions via a nonlinear convergence factor, and further improvements of the traditional Grey Wolf Optimizer algorithm through the introduction of the greedy algorithm principle and the damage repair idea in the large-scale neighborhood search algorithm.  
The specific research organization of this paper is as follows: Section 2 reviews the progress of the related research through a literature review; Section 3 analyzes the existing problems of the pharmaceutical cold chain and puts forward a cold chain transportation scheme with the dual distribution method; Section 4 designs the comparison function to determine the distribution mode and establishes a path optimization model; Section 5 introduces a large-scale neighborhood search algorithm, the Grey Wolf Optimizer (GWO), and our improvements of this algorithm; Section 6 demonstrates the superiority of our proposed method through an example analysis and an efficiency comparison with existing algorithms; Section 7 summarizes the research results and plans for future research.