scholarly journals Adaptive Multilevel Collaborative Passenger Flow Control in Peak Hours for a Subway Line

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Hongjiao Xue ◽  
Limin Jia ◽  
Jianyuan Guo
Keyword(s):  
Flow Control ◽  
Waiting Time ◽  
Large Scale ◽  
Programming Model ◽  
Control Level ◽  
Passenger Flow ◽  
Passenger Demand ◽  
Transportation Capacity ◽  
Travel Efficiency ◽  
Necessary Constraints

Due to contradiction of large-scale passenger demand and limited transportation capacity, the passengers who cannot be transported away in time accumulate and congest in stations. To ensure travel safety, improve travel efficiency, and ameliorate waiting environments for passengers, this paper proposes an adaptive multilevel collaborative passenger flow control strategy integrating the control of station entrance and station hall. An integer linear programming model is constructed, which aims at minimizing the total passenger waiting time and taking the safe capacity of each key area of all stations as the necessary constraints. The model is applied in two scenarios with different scales of passenger demand in the morning peak of the Batong line. The results show that the proposed model can adaptively activate the appropriate control level, limit the amount of accumulated passengers in each key area of the station within its safe capacity, and shorten the total passenger waiting time.

scholarly journals A Passenger Flow Routing Model for High-speed Railway Network in Different Transportation Organization Modes

2018 ◽  
Vol 30 (6) ◽  
pp. 671-682 ◽  
Author(s):  
Ying Wang ◽  
Bao-Ming Han ◽  
Jia-Kang Wang
Keyword(s):  
High Speed ◽  
Large Scale ◽  
Programming Model ◽  
Optimal Algorithm ◽  
Network Efficiency ◽  
Railway Network ◽  
High Speed Railway ◽  
Passenger Flow ◽  
Passenger Demand ◽  
Transportation Organization

Reasonable selection of passenger flow routes consideringdifferent transportation organization modes can meetthe demands of adapting to large-scale high-speed railwaynetworks and improving network efficiency. Passenger flowrouting models are developed to find and optimize a setof passenger flow routes for a high-speed railway network considering different transportation organization modes. In this paper, we presented a new approach minimizing the operating costs, including traveling cost, cost of travel time differences between different lines, and penalties for the inter-line. The network was reconstructed to solve the directed graph with four nodes (node-in-up, node-in-down, nodes-outup, and nodes-out-down) indicating one station. To tackle our problem, we presented an integer non-linear programming model, and direct passenger demand was guaranteed owing to volume constraints. Binary variables were introduced to simplify the model, and the algorithm process was optimized. We suggested a global optimal algorithm by Lingo 11.0. Finally, the model was applied to a sub-network of the Northeast China railway system. Passenger flow routes were optimized and the transportation organization mode was discussed based on passenger volume, traveling distance, and infrastructure.

Scheduling a Bus Fleet for Evacuation Planning Using Stop-Skipping Method

2021 ◽  
pp. 036119812110200
Author(s):  
Hu Zhao ◽  
Shumin Feng ◽  
Yusheng Ci
Keyword(s):  
Waiting Time ◽  
Ant Colony Algorithm ◽  
Programming Model ◽  
Peer To Peer ◽  
Mathematical Programming Model ◽  
Fleet Size ◽  
Bus Stop ◽  
Passenger Demand ◽  
Service Strategies ◽  
Bus System

Sudden passenger demand at a bus stop can lead to numerous passengers gathering at the stop, which can affect bus system operation. Bus system operators often deal with this problem by adopting peer-to-peer service, where empty buses are added to the fleet and dispatched directly to the stop where passengers are gathered (PG-stop). However, with this strategy, passengers at the PG-stop have a long waiting time to board a bus. Thus, this paper proposes a novel mathematical programming model to reduce the passenger waiting time at a bus stop. A more complete stop-skipping model that including four cases for passengers’ waiting time at bus stops is proposed in this study. The stop-skipping decision and fleet size are modeled as a dynamic program to obtain the optimal strategy that minimizes the passenger waiting time, and the optimization model is solved with an improved ant colony algorithm. The proposed strategy was implemented on a bus line in Harbin, China. The results show that, during the evacuation, using the stop-skipping strategy not only reduced the total waiting time for passengers but also decreased the proportion of passengers with a long waiting time (>6 min) at the stops. Compared with the habitual and peer-to-peer service strategies, the total waiting time for passengers is reduced by 31% and 23%, respectively. Additionally, the proportion of passengers with longer waiting time dropped to 43.19% by adopting the stop-skipping strategy, compared with 72.68% with the habitual strategy and 47.5% with the peer-to-peer service strategy.

Collaborative passenger flow control of urban rail transit network considering balanced distribution of passengers

2021 ◽  
pp. 2150461
Author(s):  
Xiang Li ◽  
Yan Bai ◽  
Kaixiong Su
Keyword(s):  
Flow Control ◽  
Programming Model ◽  
Flow Characteristics ◽  
Service Level ◽  
Urban Traffic ◽  
Urban Rail Transit ◽  
Control Measures ◽  
Rail Transit ◽  
Passenger Flow ◽  
Urban Rail

The increase of urban traffic demands has directly affected some large cities that are now dealing with more serious urban rail transit congestion. In order to ensure the travel efficiency of passengers and improve the service level of urban rail transit, we proposed a multi-line collaborative passenger flow control model for urban rail transit networks. The model constructed here is based on passenger flow characteristics and congestion propagation rules. Considering the passenger demand constraints, as well as section transport and station capacity constraints, a linear programming model is established with the aim of minimizing total delayed time of passengers and minimizing control intensities at each station. The network constructed by Line 2, Line 6 and Line 8 of the Beijing metro is the study case used in this research to analyze control stations, control durations and control intensities. The results show that the number of delayed passengers is significantly reduced and the average flow control ratio is relatively balanced at each station, which indicates that the model can effectively relieve congestion and provide quantitative references for urban rail transit operators to come up with new and more effective passenger flow control measures.

scholarly journals Analysis of the Passenger Flow Transfer Capacity of a Bus-Subway Transfer Hub in an Urban Multi-Mode Transportation Network

2020 ◽  
Vol 12 (6) ◽  
pp. 2435
Author(s):  
Yuwei Yang ◽  
Jun Chen ◽  
Zexingjian Du
Keyword(s):  
Transportation Network ◽  
Urban Traffic ◽  
Motor Vehicles ◽  
Traffic Network ◽  
Allocation Model ◽  
Passenger Flow ◽  
Transportation Capacity ◽  
Travel Efficiency ◽  
The Impact ◽  
Multi Mode

In the context of a rapid developing urban economy and the increasing number of motor vehicles, urban commuting transportation has witnessed a serious mismatch between the supply of and the demand for transportation network resources. In developing an urban multi-mode traffic network, using a urban traffic transfer hub to coordinate the transportation capabilities among different traffic networks is perceived to be highly effective for exploring the network transportation capacity of an entire transportation system, and improving travel efficiency and experiences for the public. Based on the super-network model, this paper develops a topological structure for a multi-mode traffic network, in which two typical combined travel modes are selected to establish the path impedance function for that network. Moreover, the multi-mode traffic allocation model and the solving algorithm are constructed in the research. The paper studies the impact of two types of factors related to the transfer capacity of passenger flows based on the regular traffic network of a bus-and-subway transfer hub using a sensitivity analysis of the transfer time and the associated penalty. The findings suggest that both changes in transfer walking time and the transfer penalty have no significant effect on the bus passenger flow.

scholarly journals Equity-Oriented Train Timetabling with Collaborative Passenger Flow Control: A Spatial Rebalance of Service on an Oversaturated Urban Rail Transit Line

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chaoqi Gong ◽  
Baohua Mao ◽  
Min Wang ◽  
Tong Zhang
Keyword(s):  
Flow Control ◽  
Programming Model ◽  
Optimal Solution ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Rail Transit ◽  
Optimization Approach ◽  
Train Timetabling ◽  
Passenger Flow ◽  
Urban Rail

On an oversaturated urban rail transit line, passengers at downstream stations have to wait for more trains until they get aboard, resulting in service imbalance problem. To improve the service quality, this paper proposes an integrated optimization approach combining the train timetabling and collaborative passenger flow control, with the aim of minimizing indicators associated with the passenger service imbalance and train loading capacity utilization. Considering train regulation constraints and passenger loading dynamics, a mixed-integer linear programming model is formulated. Based on the linear weighting technique, an iterative heuristic algorithm combining the tabu search and Gurobi solver is designed to solve the proposed model. Finally, a simple case with different-scale instances is used to verify that the proposed algorithm can obtain near-optimal solution efficiently. Moreover, a real-world case of Beijing Subway Batong Line is implemented to compare performances of the proposed approach with those under the original timetable and noncollaborative passenger flow control.

scholarly journals Urban Rail Timetable Optimization to Improve Operational Efficiency with Flexible Routing Plans: A Nonlinear Integer Programming Model

2019 ◽  
Vol 11 (13) ◽  
pp. 3701 ◽  
Author(s):  
Qiuchi Xue ◽  
Xin Yang ◽  
Jianjun Wu ◽  
Huijun Sun ◽  
Haodong Yin ◽  
...  
Keyword(s):  
Integer Programming ◽  
Waiting Time ◽  
Optimization Model ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Nonlinear Integer Programming ◽  
Load Factor ◽  
Integer Programming Model ◽  
Passenger Flow ◽  
Urban Rail

At present, most urban rail transit systems adopt an operation mode with a single long routing. The departure frequency is determined by the maximum section passenger flow. However, when the passenger flow varies greatly within different sections, this mode will lead to a low load factor in some sections, resulting in a waste of capacity. In view of this situation, this paper develops a nonlinear integer programming model to determine an optimal timetable with a balanced scheduling mode, where the wasted capacity at a constant departure frequency can be reduced with a slight increase in passenger waiting time. Then, we simplify the original model into a single-objective integer optimization model through normalization. A genetic algorithm is designed to find the optimal solution. Finally, a numerical example is presented based on real-world passenger and operation data from Beijing Metro Line 4. The results show that the double-routing optimization model can reduce wasted capacity by 9.5%, with a 4.5% increase in passenger waiting time, which illustrates the effectiveness of this optimization model.

scholarly journals A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty

2021 ◽  
Author(s):  
Zahra Homayouni ◽  
Mir Saman Pishvaee ◽  
Hamed Jahani ◽  
Dmitry Ivanov
Keyword(s):  
Supply Chains ◽  
Large Scale ◽  
Programming Model ◽  
Supply Chain Design ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Economic Uncertainty ◽  
Cap And Trade ◽  
Sustainable Logistics ◽  
Goal Programming Model

AbstractAdoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity. Through the development and usage of a multi-choice goal programming model solved by an improved algorithm, this article investigates sustainability strategies for carbon regulations mechanisms. We first propose a sustainable logistics model that considers assorted vehicle types and gas emissions involved with product transportation. We then construct a bi-objective model that minimizes total cost as the first objective function and follows environmental considerations in the second one. With our novel robust-heuristic optimization approach, we seek to support the decision-makers in comparison and selection of carbon emission policies in supply chains in complex settings with assorted vehicle types, demand and economic uncertainty. We deploy our model in a case-study to evaluate and analyse two carbon reduction policies, i.e., carbon-tax and cap-and-trade policies. The results demonstrate that our robust-heuristic methodology can efficiently deal with demand and economic uncertainty, especially in large-scale problems. Our findings suggest that governmental incentives for a cap-and-trade policy would be more effective for supply chains in lowering pollution by investing in cleaner technologies and adopting greener practices.

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