基于等时圈遗传启发算法的多级消防站区域优化——以南京市为例  

Multi Level Fire Station Area Optimization Based on Isochronous Circle Genetic Inspired Algorithm:Taking Nanjing as an Example

作　　者：易小雅 冯晨妤 张睿涵 任若涵 游悦佳 Yi Xiaoya;Feng Chenyu;Zhang Ruihan;Ren Ruohan;You Yuejia(School of Economics,Nanjing University of Finance and Economics,Nanjing,China)

机构地区：[1]南京财经大学经济学院,江苏南京

出　　处：《科学技术创新》2025年第10期207-210,共4页Scientific and Technological Innovation

摘　　要：本文采用等时圈遗传启发算法,从时间视角下研究了南京市多级消防站区域优化问题,发现:第一,消防站规模应与辖区内发生的火灾次数有关;第二,可以对于5 min难以到达的农村和郊区,通过完全覆盖等时圈遗传启发算法进行微型消防站的选址;第三,在消防资源有限的情况下,可以通过部分覆盖等时圈遗传启发算法,实现成本效益最大化。最终得到新增30个站点的最优多级站点配置。This article uses the isochronous circle genetic inspired algorithm to study the regional optimization problem of multi-level fire stations in Nanjing from a temporal perspective It is found that:firstly,the size of the fire station should be related to the number of fires that occur within its jurisdiction;Secondly,for rural and suburban areas that are difficult to reach within 5 minutes,a fully covered isochronous circle genetic inspired algorithm can be used to locate micro fire stations;Thirdly,in the case of limited firefighting resources,partial coverage and equal time cycle genetic heuristic algorithm can be used to achieve maximum cost-effectiveness.The optimal multi-level site configuration for adding 30 new sites was ultimately obtained.

关 键 词：遗传算法 等时圈遗传启发算法 区域优化 

分 类 号：TU998.1[建筑科学—市政工程]