Two methods based on a slight modification of the regular traffic assignmentalgorithms are proposed to directly compute turn flows instead of estimating them from link flows orobtaining them by expanding the networks....Two methods based on a slight modification of the regular traffic assignmentalgorithms are proposed to directly compute turn flows instead of estimating them from link flows orobtaining them by expanding the networks. The first one is designed on the path-turn incidencerelationship, and it is similar to the computational procedure of link flows. It applies to thetraffic assignment algorithms that can provide detailed path structures. The second utilizes thelink-turn incidence relationship and the conservation of flow on links, a law deriving from thisrelationship. It is actually an improved version of Dial's logit assignment algorithm. The proposedapproaches can avoid the shortcomings both of the estimation methods, e. g. Furness's model andFrator's model, and of the network-expanding method in precision, stability and computation scale.Finally, they are validated by numerical examples.展开更多
Computer networks and power transmission networks are treated as capacitated flow networks.A capacitated flow network may partially fail due to maintenance.Therefore,the capacity of each edge should be optimally assig...Computer networks and power transmission networks are treated as capacitated flow networks.A capacitated flow network may partially fail due to maintenance.Therefore,the capacity of each edge should be optimally assigned to face critical situations-i.e.,to keep the network functioning normally in the case of failure at one or more edges.The robust design problem(RDP)in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure.The RDP is known as NP-hard.Thus,capacity assignment problem subject to system reliability and total capacity constraints is studied in this paper.The problem is formulated mathematically,and a genetic algorithm is proposed to determine the optimal solution.The optimal solution found by the proposed algorithm is characterized by maximum reliability and minimum total capacity.Some numerical examples are presented to illustrate the efficiency of the proposed approach.展开更多
System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic...System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components;two-source two-sink network and three-source two-sink network.展开更多
The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategi...The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by rea- sonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimiza- tion problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm （MPEA） framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is pro- posed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution （CC） algorithm combined with non-dominated sorting genetic algorithm II （NSGA-II） is intro- duced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi- objective genetic algorithm （MOGA）, multi-objective evolutionary algorithm based on decom- position （MOEA/D）, CC-based multi-objective algorithm （CCMA） as well as other two MPEAs with different migration interval strategies.展开更多
This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dy...This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.展开更多
多层大型地库车流量大且交通组织复杂,对交通流线设计与优化具有较高的要求。为提升车辆在地库中的通行效率并减少出库时间,研究了基于交通仿真分析的地库流线优化方法。基于多层大型地库路网,将地库车位与出口分别当作起点(origin,O)...多层大型地库车流量大且交通组织复杂,对交通流线设计与优化具有较高的要求。为提升车辆在地库中的通行效率并减少出库时间,研究了基于交通仿真分析的地库流线优化方法。基于多层大型地库路网,将地库车位与出口分别当作起点(origin,O)和终点(destination,D),构建分时段的OD需求数据,选取动态系统最优交通分配(dynamic system optimal,DSO)算法按照给定的流线设计方案对地库路网车流进行分配加载,并基于车流动态加载结果对流线设计方案进行评估。在流线优化过程中,优先考虑上下层的关键通道的流线设计形式(如单双向或上下行等),然后着重考虑地库出口附近的交通冲突,遵从交通冲突点越少越好的设计原则,最后将满足双向通行条件的路段改成双向通行,以增加路网通行能力。在数值实验中,针对北京市某商品房小区双层大型地库,使用城市交通能力仿真软件(simulation of urban mobility,SUMO)搭建地库微观交通仿真平台,并根据实际数据构造时变随机OD出库需求,通过仿真分析对比了流线设计方案优化前后的路网总旅行时间、出口总排队时间、关键拥堵路段的排队时间等,进一步仿真分析了流线优化方案在突发应急状况下(如出口数量变化、OD出库需求突增)的鲁棒性能。实验结果验证了流线优化方案有助于提升地库通行效率,并具有良好的应急能力。展开更多
Passenger flow is the foundation for urban rail transit(URT)operations.However,its cal-culated results from assignment models may deviate from the actual situation in both spa-tial and temporal dimensions,which arouse...Passenger flow is the foundation for urban rail transit(URT)operations.However,its cal-culated results from assignment models may deviate from the actual situation in both spa-tial and temporal dimensions,which arouses more attention and needs to be evaluated in particular.On the other hand,onboard video data from URT trains provides a potential way for model evaluation.This study defines the evaluation problem,and proposes a method-ological solution for evaluating rail transit assignment models in the temporal dimension,which includes qualitative validation and difference quantification.A suitable time granu-larity is determined for the best effectiveness,and onboard video data are used for actual passenger flow extraction.The gap between the actual and calculated data by the model is identified with nonparametric statistical techniques(NPSTs)and quantified with time ser-ies similarity measurement(TSSM)methods.A case study on the Shanghai metro demon-strates the performance of the proposed approach,and several practice implications for URT operation agencies are discussed.展开更多
文摘Two methods based on a slight modification of the regular traffic assignmentalgorithms are proposed to directly compute turn flows instead of estimating them from link flows orobtaining them by expanding the networks. The first one is designed on the path-turn incidencerelationship, and it is similar to the computational procedure of link flows. It applies to thetraffic assignment algorithms that can provide detailed path structures. The second utilizes thelink-turn incidence relationship and the conservation of flow on links, a law deriving from thisrelationship. It is actually an improved version of Dial's logit assignment algorithm. The proposedapproaches can avoid the shortcomings both of the estimation methods, e. g. Furness's model andFrator's model, and of the network-expanding method in precision, stability and computation scale.Finally, they are validated by numerical examples.
文摘Computer networks and power transmission networks are treated as capacitated flow networks.A capacitated flow network may partially fail due to maintenance.Therefore,the capacity of each edge should be optimally assigned to face critical situations-i.e.,to keep the network functioning normally in the case of failure at one or more edges.The robust design problem(RDP)in a capacitated flow network is to search for the minimum capacity assignment of each edge such that the network still survived even under the edge’s failure.The RDP is known as NP-hard.Thus,capacity assignment problem subject to system reliability and total capacity constraints is studied in this paper.The problem is formulated mathematically,and a genetic algorithm is proposed to determine the optimal solution.The optimal solution found by the proposed algorithm is characterized by maximum reliability and minimum total capacity.Some numerical examples are presented to illustrate the efficiency of the proposed approach.
文摘System reliability optimization problem of multi-source multi-sink flow network is defined by searching the optimal components that maximize the reliability and minimize the total assignment cost. Therefore, a genetic-based approach is proposed to solve the components assignment problem under budget constraint. The mathematical model of the optimization problem is presented and solved by the proposed genetic-based approach. The proposed approach is based on determining the optimal set of lower boundary points that maximize the system reliability such that the total assignment cost does not exceed the specified budget. Finally, to evaluate our approach, we applied it to various network examples with different numbers of available components;two-source two-sink network and three-source two-sink network.
基金co-supported by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 60921001)
文摘The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by rea- sonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimiza- tion problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm （MPEA） framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is pro- posed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution （CC） algorithm combined with non-dominated sorting genetic algorithm II （NSGA-II） is intro- duced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi- objective genetic algorithm （MOGA）, multi-objective evolutionary algorithm based on decom- position （MOEA/D）, CC-based multi-objective algorithm （CCMA） as well as other two MPEAs with different migration interval strategies.
文摘This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.
文摘多层大型地库车流量大且交通组织复杂,对交通流线设计与优化具有较高的要求。为提升车辆在地库中的通行效率并减少出库时间,研究了基于交通仿真分析的地库流线优化方法。基于多层大型地库路网,将地库车位与出口分别当作起点(origin,O)和终点(destination,D),构建分时段的OD需求数据,选取动态系统最优交通分配(dynamic system optimal,DSO)算法按照给定的流线设计方案对地库路网车流进行分配加载,并基于车流动态加载结果对流线设计方案进行评估。在流线优化过程中,优先考虑上下层的关键通道的流线设计形式(如单双向或上下行等),然后着重考虑地库出口附近的交通冲突,遵从交通冲突点越少越好的设计原则,最后将满足双向通行条件的路段改成双向通行,以增加路网通行能力。在数值实验中,针对北京市某商品房小区双层大型地库,使用城市交通能力仿真软件(simulation of urban mobility,SUMO)搭建地库微观交通仿真平台,并根据实际数据构造时变随机OD出库需求,通过仿真分析对比了流线设计方案优化前后的路网总旅行时间、出口总排队时间、关键拥堵路段的排队时间等,进一步仿真分析了流线优化方案在突发应急状况下(如出口数量变化、OD出库需求突增)的鲁棒性能。实验结果验证了流线优化方案有助于提升地库通行效率,并具有良好的应急能力。
基金supported by the National Natural Science Foundation of China(Nos.72071147 and 71701152)the Fundamental Research Funds for the Central Universities of China(No.22120220628).
文摘Passenger flow is the foundation for urban rail transit(URT)operations.However,its cal-culated results from assignment models may deviate from the actual situation in both spa-tial and temporal dimensions,which arouses more attention and needs to be evaluated in particular.On the other hand,onboard video data from URT trains provides a potential way for model evaluation.This study defines the evaluation problem,and proposes a method-ological solution for evaluating rail transit assignment models in the temporal dimension,which includes qualitative validation and difference quantification.A suitable time granu-larity is determined for the best effectiveness,and onboard video data are used for actual passenger flow extraction.The gap between the actual and calculated data by the model is identified with nonparametric statistical techniques(NPSTs)and quantified with time ser-ies similarity measurement(TSSM)methods.A case study on the Shanghai metro demon-strates the performance of the proposed approach,and several practice implications for URT operation agencies are discussed.
