## 1 Introduction  
Rural roads in foreign countries are typically referred to as county, township, and village or low-volume roads in China. Rural roads are a critical component of China's road network, essential for rural economic and social development. China began large-scale rural road construction in 2003, with a total length of 4.5314 million kilometers by the end of 2022, accounting for 84.6% of all roads. A developed rural highway transportation network has been established, centered around county towns, with townships as nodes and village groups as the network. In recent years, rural road development in China has shifted from construction to maintenance due to the rapid growth of the scale of rural road construction. With limited maintenance funds, local road management departments face challenges in managing such a vast mileage of rural roads effectively while improving maintenance fund utilization efficiency and guaranteeing road service levels. The current maintenance and management system applies high-grade road maintenance decision-making without considering differences in pavement structure, traffic volume, and funding budgets, leading to issues like unreasonable pavement performance evaluations and inadequate scientific maintenance decision-making in actual management processes. Therefore, it is necessary to establish a decision-making method for rural road surface maintenance through systematic research. Selectively locating maintenance sections and measures can effectively maintain a high level of service for rural roads. Research on low-flow rural road maintenance decision-making has been conducted abroad. [PERSON] [1] et al. (2010) used Geographic Information System (GIS) to determine the priority map of pavement maintenance in the Himalayas and developed a budget, time, and resource-constrained decision model for rural road maintenance. [PERSON] [2] et al. (2012) evaluated pavement conditions using the Pavement Condition Index (PCI) and adopted a \"worst PCI priority\" strategy for Sudan's rural road networks. [PERSON] [3] et al. (2015) created a dual-objective deterministic optimization model for rural road network maintenance and proposed a constrained genetic algorithm as the optimization tool. [PERSON] [4] et al. (2017) studied the impact of road environmental performance on road maintenance decision management, integrating technical, economic, and environmental aspects into maintenance plan design, and developed a tool for SUS optimization design. [PERSON] [5] et al. (2017) studied Indian rural roads and found that maintenance decisions primarily depend on functional, structural, and importance conditions, proposing a two-stage optimization process. [PERSON] [6] et al. (2020) established a multi-objective decision-making framework based on pavement structure type selection to address funding, technology, and human resource issues in low-traffic rural road maintenance, providing tools for local highway planning and decision-making. [PERSON] [7] et al. (2023) researched and developed a long-term rural road network planning method, applied ant colony optimization, and found it to be 14% more efficient than existing models through verification analysis. Pavement maintenance decision-making has widely employed various methods, from simple ranking to complex mathematical planning. However, each method has limitations in solving real-world optimization problems. For instance, the ranking method is straightforward but lacks holistic conservation planning over the entire period. It struggles with sorting multiple objectives ([PERSON] [8] et al. 2014, [PERSON] [9] 2015, [PERSON] [10] et al. 2019). The mathematical planning model considers different sections, schemes, and time series within the road network but suffers from unstable solutions and slow processing for large-scale problems ([PERSON] [11] et al. 2021).