## 1 Introduction  
In order to enhance the efficiency of rescue operations and improve the survival rates of disaster sufferers, it is essential to reserve emergency supplies [1]. Likewise, the reserve of supplies holds critical significance for a country's military, economic, and social security [2]. How to achieve optimal resource allocation, enhance the efficiency of emergency supply reserve warehouses, scientifically evaluate existing emergency supply reserve warehouses, and optimize site selection are significant practical issues that require immediate resolution. Extensive studies have been conducted by scholars both in China and abroad on the evaluation and optimization of site selection for emergency supply reserve warehouses. The optimization of emergency facilities is influenced by a multitude of complex factors. Some scholars utilized Data Envelopment Analysis (DEA) [3; 4; 5] to analyze various quantitative indicators that impact the input and output of site selection for emergency facilities. Most scholars employed multi-attribute decision-making techniques, such as fuzzy mathematics theory [6; 7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18], Analytic Hierarchy Process (AHP) [14; 16; 18; 19; 20; 21], and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) [16; 22; 23; 24; 25; 26]. Most scholars have considered the impact of economic, safety, service, and social factors on emergency supply reserve warehouses. While the aforementioned methods can rank alternative sites based on their superiority or inferiority, they do not offer a correct decision on the suitability of a site for establishing an emergency supply reserve warehouse. To uncover important information included in observational data of emergency systems, this study pioneers the application of the multi-attribute weighted intelligent gray target decision-making evaluation model to the optimization of site selection for emergency supply reserve warehouses. [PERSON] [27] first introduced the concept of gray system theory. Building on the foundation of four types of uniform effect measure functions, [PERSON] et al. [28] proposed the multi-attribute weighted gray target decision model. This model assists decision-makers in selecting the optimal decision from multiple objectives under conditions of limited information and sparse data. Currently, this model has been applied across various fields, yielding impressive outcomes. Examples include the selection of supply chain suppliers [29; 30], maintenance decision for power transformers [31], selection of weapon procurement plans for artillery weaponry for a military unit [32], determination of the optimal mix ratio [33], selection of energy-saving service providers [34], synthetic effect measures of the leading industry objective system in the Kashgar urban agglomeration [35], fault localization [36], emergency plan selection after the outbreak of public health incidents [37], risk assessment for coal and gas outbursts [38], multi-attribute scheduling for mixed-flow production workshops of missile components [39], and the tendering process for civilian biogas energy projects [40]. Beyond theoretical discussions, the application of these methods is equally important. Some scholars have implemented these methods to optimize the allocation of emergency supply reserve warehouses at the national, municipal, and town levels [41; 42; 43; 44]. This study utilizes the multi-attribute weighted intelligent gray target decision-making evaluation model for a comprehensive evaluation of the site selection for emergency supply reserve warehouses. Subsequently, the site selection is optimized based on the evaluation results. The innovations of this paper include the following:  
1. It introduces a new evaluation method for the site selection of emergency supply reserve warehouses--the multi-attribute weighted intelligent gray target decision-making evaluation model.