基于改进蚁群算法的山区输油管道泄漏抢险路径规划  

Path planning for urgent repair in response to oil pipeline leaks in mountainous areas based on improved ant colony algorithm

作　　者：蒋宏业 王盛涛 冷朝晖 徐涛龙 张乐园 JIANG Hongye;WANG Shengtao;LENG Chaohui;XU Taolong;ZHANG Leyuan(School of Oil&Natural Gas Engineering,Southwest Petroleum University;CNAF Pengzhou Pipeline Transportation Co.,Ltd.)

机构地区：[1]西南石油大学石油与天然气工程学院 [2]中航油彭州管道运输有限公司

出　　处：《管道保护》2025年第2期51-61,共11页

摘　　要：山区输油管道在突发泄漏时,由于地形复杂、道路稀疏及环境敏感度高等原因,抢险工作往往面临严峻挑战。针对此问题提出了一种改进蚁群算法(Improved Ant Colony Optimization,I-ACO),通过构建融合地形阻力、泄漏风险与环境敏感度的综合成本函数,将多维约束定量化,并引入动态信息素挥发率、已有道路先验偏好及局部搜索策略,以提高算法收敛速度并减少陷入局部最优的可能。仿真结果表明,在20×20网格测试中,I-ACO在已有道路与环境敏感区等多场景下的收敛速度比传统蚁群算法最高提升60.0%,敏感区穿越减少57.1%;在200×200真实地形映射中,收敛速度提升17.5%,路径更倾向于选取平缓及风险较低区域,更符合应急抢险需求。该研究可为山区输油管道泄漏抢险提供高效、可靠的路径优化方法。Sudden leaks in oil pipelines situated in mountainous areas present significant challenges for urgent repairs due to complex terrain,limited road access,and highly sensitive environmental conditions.To address these challenges,this paper presents an improved ant colony algorithm(I-ACO).This approach introduces a composite cost function that integrates ter‐rain resistance,leakage risk,and environmental sensitivity.Additionally,the function incorporates quantified multidimensional constraints,dynamic pheromone evaporation rates,prior preferences for existing roads,and local search strategies.As a result,the algorithm is enhanced to improve the convergence rate while reducing the likelihood of converging to local optima.The simulation results indicated that the convergence rate of the I-ACO was 60.0%higher and the rate of traversing sensitive ar‐eas was 57.1%lower in 20×20 grid tests compared to traditional ant colony algorithms,across multiple scenarios involving existing roads and environmentally sensitive areas.In a 200×200 real-scenario terrain mapping,the convergence rate in‐creased by 17.5%,and the likelihood of selecting paths through flat,low-risk areas rose,enhancing the algorithm's adaptabil‐ity to urgent repair needs.These findings offer an efficient and reliable path optimization approach for urgent repairs in re‐sponse to oil pipeline leaks in mountainous areas.

关 键 词：山区输油管道 路径算法 蚁群算法 数字高程模型(DEM) 泄漏抢险 

分 类 号：TE89[石油与天然气工程—油气储运工程]