航站楼内多目标路径规划方法设计与实现

Design and implementation of multi-objective path planning method in terminal

针对航站楼多楼层的室内导航和多目标的路径优化问题,提出一种基于改进遗传算法的航站楼内交通换乘导航路径规划方法:依据航站楼内的空间特征和环境变化建立以路径为权值和以人流密度为权值的双路网,并权衡路径的距离成本、客流拥挤度和时间成本3种因素,建立了航站楼内的多目标路径优化模型.最后使用融合广度优先搜索策略(Breadth First Search,BFS)的遗传算法在本文构建的多层路网中实现航站楼内多目标路径优化,生成考虑路径距离、拥挤度、时间成本的单目标最优路径和多目标优化路径.研究结果表明,使用融合BFS的遗传算法在本文构建的多层路网中可实现航站楼内多目标路径优化,生成考虑路径距离、拥挤度、时间成本的单目标最优路径和多目标优化路径.

Facing the problem of multi-floor indoor navigation and multi-objective path optimization in a terminal building,this paper presents a method of navigation route planning for traffic transfer in a terminal building based on an improved genetic algorithm.According to the spatial characteristics and environmental changes in the terminal building,this paper establishes a two-way network with path and flow density as the weight,and weighs the three factors of path distance cost,passenger flow congestion and time cost,then establishes a multi-objective path optimization model in the terminal.Finally,this paper uses genetic algorithm fused with BFS to achieve multi-objective path optimization in the terminal building in the multi-level road network constructed,and generates single-objective optimal paths and multi-objective optimized paths considering path distance,congestion,and time cost.he results show that genetic algorithm fused with BFS could achieve multi-objective path optimization in the terminal building in the multilevel road network constructed in this paper,and generates single-objective optimal paths and multi-objective optimized paths considering path distance,congestion,and time cost.