Simulation-Based Optimization in a Bidirectional $A/B$ Skip-Stop Bus Service

Huang, Qingxia; Jia, Bin; Jiang, Rui; Qiang, Shengjie

doi:10.1109/access.2017.2731384

Cited by 21 publications

(11 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, we propose a model for generating the stopskipping schemes during large crowding events. e proposed model belongs to nonlinear integer programming models [32], which were often used in urban metro management [18,19] and public transportation management [33,34]. In Section 2.1, we make a general problem statement.…”

Section: Model Formulationmentioning

confidence: 99%

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Zhou

Zheng

Cen

et al. 2021

Journal of Advanced Transportation

View full text Add to dashboard Cite

Large crowding events in big cities pose great challenges to local governments since crowd disasters may occur when crowd density exceeds the safety threshold. We develop an optimization model to generate the emergent train stop-skipping schemes during large crowding events, which can postpone the arrival of crowds. A two-layer transportation network, which includes a pedestrian network and the urban metro network, is proposed to better simulate the crowd gathering process. Urban smartcard data is used to obtain actual passenger travel demand. The objective function of the developed model minimizes the passengers’ total waiting time cost and travel time cost under the pedestrian density constraint and the crowd density constraint. The developed model is tested in an actual case of large crowding events occurred in Shenzhen, a major southern city of China. The obtained train stop-skipping schemes can effectively maintain crowd density in its safety range.

show abstract

Section: Model Formulationmentioning

confidence: 99%

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Zhou

Zheng

Cen

et al. 2021

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…$,' = 1, ∀ , = 1, = (10) and (11) define the binary nature of the assignment variables for vehicle type and stops to lines, respectively, already defined in Table 1; (12) restricts a homogenous fleet assignment per line; (13) defines the capacities of the vehicles being used in the model; (14) is applied where there is a constraint on the number of vehicles of each type; (15) guarantees the sufficient supply of the system for the given solution to satisfy the demand, although this is already implicitly considered in the lower level assignment model; (16) establishes the lower limit of the frequency values; (17) makes sure that all the stops are serviced by at least one line; (18) obliges all the lines to run the entire length of the corridor; (19) guarantees the capacity constraint of the vehicles at the stops and (20) represents the operator budgetary constraints. This research does not consider constraints (14) and (20).…”

Section: B Upper Level: Cost Functionmentioning

confidence: 99%

“…They may propose: (i) a bi-level optimization model with an objective function on the upper level (usually based on the minimization of a user and operator cost function) and they use a passenger assignment algorithm for the public transport service (deterministic or stochastic) on the lower level (with or without the consideration of transfers and capacity constraints) or (ii) the optimization of a unique cost function incorporating the capacity constraint as a problem constraint. Alternative approaches has also proposed simulation based optimization techniques [19]. They are applied to real or quasi-real corridors after their application to a test corridor and they may or may not consider the presence of transfers in their models.…”

Section: Introductionmentioning

confidence: 99%

Limited Stop Services Design Considering Variable Dwell Time and Operating Capacity Constraints

et al. 2021

View full text Add to dashboard Cite

This article proposes an optimization model to set frequencies, vehicle capacities, required fleet and the stops serving each route along a transit corridor which minimize the total user and operating costs. The optimization problem is solved by applying the "Black Hole" algorithm, which imitates the movement of stars (solutions), towards a black hole (Best solution). The main contributions of the model are based on incorporating variable dwell times depending on bus stop demand not only to the passenger perceived journey times but also to the bus cycle times and on considering capacity constraints in both vehicles and bus tops. This led to a more accurate and realistic operating times and user perceived journey times. The application of the model to two case studies and the sensitivity analysis carried out demonstrate that for low levels of demand, constant dwell times can be assumed but being these times different between the different stops of the corridor, considering their demand. However, with high level of demand the difference found in operating costs and travel times strongly recommend incorporating variable dwell times in the model in order to achieve a more realistic design of transit corridor strategies. INDEX TERMS Limited stop services, Bus Rapid Transit, dwell time, express services, transit corridor, Black Hole algorithm.

show abstract

“…In Constraint (7) and (8), the departure and arrival times of the first express trains, which includes the product of stopping decision variables and dwell times, are expressed as quadratic constraints. We introduce another five linear constraints to substitute Constraint (2), (7) and (8) as follows.…”

Section: ) Departure and Arrival Time Of Express Trainsmentioning

confidence: 99%

Integrated Optimization of Train Stop Planning and Scheduling on Metro Lines With Express/Local Mode

Mao

Bai

et al. 2019

IEEE Access

View full text Add to dashboard Cite

Train stopping patterns and schedules play critical roles in the service design of metro lines with express/local mode. Previous studies on express/local mode generally handle the design of train stopping patterns and schedules independently, which cannot ensure the overall optimality of service provision. In this paper, a mixed integer nonlinear programming model is developed to collaboratively adjust train stopping patterns and schedules in order to minimize passenger travel time in express/local mode. With two types of train services provided, overtaking is allowed and a diverse set of passenger route choices is also incorporated into the proposed model. Linearization techniques are applied to transform this model from nonlinear to linear, which enables the proposed model to be handled by commercial linear solvers. To enhance computing efficiency in large-scale problems, a guided branch-and-cut algorithm is designed. The numerical examples on a test line and a real-world metro line are implemented to demonstrate the effectiveness of the proposed model and approach. The proposed approach is compared to existing approaches to identify the benefits of integrating train stop planning and scheduling decisions. Based on the computational time and the objective value, the guided branch-and-cut algorithm outperforms the direct use of the CPLEX solver. INDEX TERMS Public transportation, train stop planning, train scheduling, express/local mode, integrated optimization, mixed integer linear programming.

show abstract

Simulation-Based Optimization in a Bidirectional $A/B$ Skip-Stop Bus Service

Cited by 21 publications

References 17 publications

A Data-Driven Urban Metro Management Approach for Crowd Density Control

A Data-Driven Urban Metro Management Approach for Crowd Density Control

Limited Stop Services Design Considering Variable Dwell Time and Operating Capacity Constraints

Integrated Optimization of Train Stop Planning and Scheduling on Metro Lines With Express/Local Mode

Contact Info

Product

Resources

About