旅游高峰期景区游客旅游路线调度方法分析
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摘要
在旅游高峰期,为了降低游客拥堵,需要进行旅游路线的优化调度,提出基于并行网格分割的旅游高峰期景区游客旅游路线调度方法,构建旅游高峰期景区游客旅游路线的路网结构模型,采用并行算法进行旅游路线的拥堵程度和负载评估,采用量化均衡控制方法进行景区游客路路线的均衡配置,根据景区的人流密度进行线路信息融合处理,采用全局寻优方法进行旅游高峰期景区游客旅游路线的网格分割,在全局组网模型下实现对旅游高峰期景区游客旅游路线的优化调度。仿真结果表明,采用该方法进行旅游高峰期景区游客旅游路线调度的均衡配置性能较好,拥堵程度下降,提高了景区的畅通性。
In order to reduce the tourist congestion during the peak period of tourism,we need to carry out the optimal scheduling of tourist routes,and put forward the scheduling method of tourist routes of tourist peak areas based on parallel grid segmentation. The paper constructs the network structure model of tourist route of tourist peak area,adopts parallel algorithm to evaluate the congestion degree and load of tourist route,and adopts quantitative equilibrium control method to carry out the balanced allocation of tourist route of scenic spot. According to the density of the tourist flow,the route information is fused and the global optimization method is used to segment the tourist route of the tourist route in the tourist peak area. Under the global networking model,the optimal scheduling of tourist routes in tourist peak scenic spots is realized. The simulation results show that the proposed method has a good performance in the balanced allocation of tourist routes in the peak tourist spots,and the congestion degree is reduced. Improve the smooth flow of scenic spots.
In order to reduce the tourist congestion during the peak period of tourism,we need to carry out the optimal scheduling of tourist routes,and put forward the scheduling method of tourist routes of tourist peak areas based on parallel grid segmentation. The paper constructs the network structure model of tourist route of tourist peak area,adopts parallel algorithm to evaluate the congestion degree and load of tourist route,and adopts quantitative equilibrium control method to carry out the balanced allocation of tourist route of scenic spot. According to the density of the tourist flow,the route information is fused and the global optimization method is used to segment the tourist route of the tourist route in the tourist peak area. Under the global networking model,the optimal scheduling of tourist routes in tourist peak scenic spots is realized. The simulation results show that the proposed method has a good performance in the balanced allocation of tourist routes in the peak tourist spots,and the congestion degree is reduced. Improve the smooth flow of scenic spots.
引文
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[2]陈秀锋,许洪国,倪安宁.并行微观交通动态负载平衡预测方法仿真[J].计算机仿真,2013,30(8):164-168.
[3]薛明,许德刚.基于云网格集成调度的防拥堵车辆路径规划算法[J].计算机科学,2015,42(7):295-299.
[4]彭丽英.改进滑模干扰控制律交通数据反步融合算法[J].控制工程,2014,21(4):515-519.
[5]许晓玲.基于物联网模糊评估的大型交通车辆调度模型研究[J].科技通报,2013,29(10):189-192.
[6]WEI S and LIN Z.Accelerating iterations involving eigenvalue or singular value decomposition by block lanczos with warm start[R].Seattle:Microsoft Corp.,2010.
[7]LEE S J and OUYANG C S.A neuro-fuzzy system modeling with self-constructing rule generation and hybrid SVD-based learning[J].IEEE Transaction of Fuzzy Systems,2003,11(3):341-353.
[8]Leontiadis I,Marfia G,Mack D,et al.On the effectiveness of an opportunistic traffic management system for vehicular networks[J].IEEE Transactions on Intelligent Transportation Systems,2011,12(4):1537-1548.
[9]SHEN Wei,WYNTER L.A New One-level Convex Optimization Approach for Estimating Origin-destination Demand[J].Transportation Research Part B:Methodological,2012,46(10):1535-1555.
[10]SUN Huijun,ZHANG Hui,and WU Jianjun.Correlated scale-free network with community:modeling and transportation dynamics[J].Nonlinear Dynamics,2012,69(4):2097-2104.
[11]王光浩,吴越.一种车载自组织网络路况信息的数据信任模型[J].计算机科学,2014,41(6):89-93.
[12]彭雅丽,章志明,宋彦婷.基于网络演算的智能交通流量分配研究[J].计算机应用研究,2012,29(8):2891-2894.
[13]SHEN Wei,WYNTER L.A New One-level Convex Optimization Approach for Estimating Origin-destination Demand[J].Transportation Research Part B:Methodological,2012,46(10):1535-1555.
[14]张晨,张宁.上海市公交网络拓扑性质研究[J].上海理工大学学报,2006,28(5):489-494.
[15]惠伟,王红.复杂网络在城市公交网络中的实证分析[J].计算机技术与发展,2008,18(11):217-219.
[16]宗跃光,陈眉舞,杨伟,等.基于复杂网络理论的城市交通网络结构特征[J].吉林大学学报:工学版,2009,39(4):910-915.
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