基于改进遗传算法的路网应急疏散多目标优化  

Multi-objective Optimization of Emergency Evacuation Using Improved Genetic Algorithm

作　　者：孟永昌 杨赛霓[1,2] 史培军[1,2] 

机构地区：[1]北京师范大学地表过程与资源生态国家重点实验室,北京100875 [2]民政部/教育部减灾与应急管理研究院,北京100875

出　　处：《武汉大学学报（信息科学版）》2014年第2期201-205,共5页Geomatics and Information Science of Wuhan University

基　　金：高等学校博士学科点专项科研基金资助项目(20100003120029);国家科技部国际科技合作资助项目(2012DFG20710)~~

摘　　要：基于路网应急疏散问题的实际需求,提出以路径流量为决策变量,以疏散流量最大、疏散路线最短和可靠性最高为目标的多目标优化模型,综合考虑了应急疏散的时效性、经济性和安全性,并设计自适应小生境Pareto遗传算法对模型进行求解。以某地区实际路网为例进行模拟分析,验证了算法的有效性和可行性。Based on the actual demands of emergency evacuation, this paper establishes a multi-objective optimization model which takes the flow of each path as a control variable. Maximum flow, minimum cost, and maximum reliability are considered as objectives to integrate the timeliness, economy and security of emergency evacuation. An improved Pareto multiple objective genetic algorithm is pro- posed, to encode the control variables directly. It introduces a fitness function based on the degree of Pareto domination and self-adaption punishment, and designs a selection operator based on tourna- ment and niche technology. The algorithm provides a practical tool to solve the problem with complex constraints and multiple objectives. Finally, a real world road network is used for simulation and analyses, which validates the effectiveness and applicability of the proposed methodology.

关 键 词：应急疏散 多目标 遗传算法 最短路 可靠性中图法 

分 类 号：P208[天文地球—地图制图学与地理信息工程]