基于递阶多目标规划的宏、微观消防站选址方法
A Hierarchical Multi-Objective Programming Approach to Planning Locations for Macro and Micro Fire Stations
摘要：
消防站是城市应急控制系统中最关键的应急设施之一，具有快速应对火灾等突发事件的能力。消防站的选址规划对消防站的应急响应能力和效率有着重要的影响，同时也影响着建设成本。为了获得高效实用的消防站选址方案，选址模型中需要考虑效用最大化、距离约束和工作量限制等主要要求，特别是对于具有特定目标和建设要求的宏观和微观消防站的多级消防设施系统。本文提出了一种新的分层优化方法，考虑所有的主要要求，位置规划和债券之间的功能连接不同级别的消防站在同一时间。建立了单目标和多目标最优化模型，同时解决了宏观和微观消防站选址问题。采用保留精英的遗传算法和基于Pareto的多目标进化算法来求解该问题。以深圳市福田区为例，对所提出的分层选址模型进行了验证，结果表明了该方法的有效性和实用性。
英文摘要：
Fire stations are among the most crucial emergency facilities in urban emergency control system in terms of their quick response to fires and other emergencies. Location plannings for fire stations have a significant influence on their effectiveness and capability of emergency responses trading off with the cost of constructions. To obtain efficient and practical siting plans for fire stations, various major requirements including effectiveness maximization, distance constraint and workload limitation are required to be considered in location models, especially for multi-level fire facility systems with macro and micro fire stations having specific aims and construction requirements. This paper proposes a novel hierarchical optimization approach taking all the major requirements for location planning into consideration and bonds functional connections between different levels of fire stations at the same time. A single-objective and a multi-objective optimization model are established to solve the location siting problems for macro and micro fire stations simultaneously. Genetic algorithm with elitist reservation and Pareto-based multi-objective evolutionary algorithm are adopted to solve the problem with NP-hard nature. The proposed hierarchical location model is further performed in a case study of Futian District in Shenzhen, and the siting result justifies the effectiveness and practicality of our novel approach.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
