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 EvacuationUsing Improved Genetic Algorithm

  • 摘要: 目的 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。

     

    Abstract: Objective Based on the actual demands of emergency evacuation,this paper establishes a multi-objec-tive optimization model which takes the flow of each path as a control variable.Maximum flow,mini-mum cost,and maximum reliability are considered as objectives to integrate the timeliness,economyand 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 ofPareto 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 complexconstraints and multiple objectives.Finally,a real world road network is used for simulation and ana-lyses,which validates the effectiveness and applicability of the proposed methodology.

     

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