Coordination of Feeder Bus Schedule with Train Service at Integrated Transport Hubs

2017 ◽  
Vol 2648 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Xueping Dou ◽  
Xiaolin Gong ◽  
Xiucheng Guo ◽  
Tao Tao
Keyword(s):  
Urban Rail Transit ◽  
Operating Costs ◽  
Mixed Integer ◽  
Decision Variable ◽  
Coordination Problem ◽  
Schedule Coordination ◽  
Feeder Bus ◽  
Minlp Model ◽  
Bus Service ◽  
Bus Schedule

This paper proposes a schedule coordination method for transfer problems between an urban rail transit service and its feeder bus service. For given train schedules, a novel mixed-integer nonlinear programming (MINLP) model is formulated to obtain a coordinated bus schedule with the objective of minimizing the weighted sum of passenger transfer costs and bus operating costs. The queuing process for transfer passengers at the transport hubs, which is attributed to both high transfer volumes and limited bus capacity, is discussed and considered in the coordination problem. The vital decision variable is the terminal departure time of each target feeder bus trip within a certain time period. A hybrid solution method that integrates heuristic and enumerative algorithms was developed to solve the MINLP model, and numerical experiments were conducted for different scenarios. The results indicate that the feeder bus schedule coordinated by the developed model is capable of substantially reducing the transfer waiting time for train passengers with a slight increase in bus operating costs.

Schedule Coordination Method for Last Train Transfer Problem

2017 ◽  
Vol 2648 (1) ◽  
pp. 86-95 ◽  
Author(s):  
Xueping Dou ◽  
Xiucheng Guo
Keyword(s):  
Transfer Problem ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Transit System ◽  
Schedule Coordination ◽  
Urban Rail ◽  
Integer Nonlinear Programming ◽  
Minlp Model ◽  
Optimization Solvers

This paper proposes a schedule coordination method for last train service in an urban rail transit system. The method offsets and perturbs the original train schedule to reduce transfer failures across different lines, and it considers the effect of schedule adjustments. The proposed problem is formulated as a mixed-integer nonlinear programming (MINLP) model. The MINLP model is equivalently transformed into a mixed-integer linear programming (MILP) model that can be exactly solved by commercial optimization solvers. A case study based on the mass rapid transit system in Singapore was conducted. The results of the case study indicate that the train schedule that is coordinated by the developed model is capable of substantially improving operational connectivity. Therefore, the model proposed in this study can be employed as a viable tool to assist with the coordination of train schedules for public transport operators.

Feeder Bus Timetable Design and Vehicle Size Setting in Peak Hour Demand Conditions

2019 ◽  
Vol 2673 (10) ◽  
pp. 321-332 ◽  
Author(s):  
Xueping Dou ◽  
Qiang Meng
Keyword(s):  
Mixed Integer ◽  
Arrival Times ◽  
Non Linear Programming ◽  
Bee Colony ◽  
Proposed Model ◽  
Feeder Bus ◽  
Minlp Model ◽  
Failure Cost ◽  
Set Up ◽  
The Given

This study proposes a solution to the feeder bus timetabling problem, in which the terminal departure times and vehicle sizes are simultaneously determined based on the given transfer passengers and their arrival times at a bus terminal. The problem is formulated as a mixed integer non-linear programming (MINLP) model with the objective of minimizing the transfer waiting time of served passengers, the transfer failure cost of non-served passengers, and the operating costs of bus companies. In addition to train passengers who plan to transfer to buses, local passengers who intend to board buses are considered and treated as passengers from virtual trains in the proposed model. Passenger attitudes and behaviors toward the waiting queue caused by bus capacity constraints in peak hour demand conditions are explicitly embedded in the MINLP model. A hybrid artificial bee colony (ABC) algorithm is developed to solve the MINLP model. Various experiments are set up to account for the performance of the proposed model and solution algorithm.

scholarly journals Optimal Operation Scheme with Short-Turn, Express, and Local Services in an Urban Rail Transit Line

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Tao Feng ◽  
Siyu Tao ◽  
Zhengyang Li
Keyword(s):  
Search Algorithm ◽  
Real Life ◽  
Optimal Operation ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Rail Transit ◽  
Nonlinear Program ◽  
Urban Rail ◽  
Local Services ◽  
Minlp Model

Flexible railway operation modes combining different operation strategies, such as short-turn, express, and local services, can significantly reduce operator and user costs and increase the efficiency and attractiveness of rail transit services. It is therefore necessary to develop optimization models to find optimal combinations of operation strategies for urban rail transit lines. In this paper, a model is proposed for solving the urban rail transit operation scheme problem. The model considers short-turn, express, and local services with the aim of minimizing the operator’s and users’ costs. The problem is first decomposed into two subproblems: the service route design problem and the passenger assignment problem. Then, a mixed-integer nonlinear program (MINLP) model is formulated, and linearization techniques are utilized to transform the MINLP model into a mixed-integer linear programming (MILP) model that can be easily solved by commercial optimization solvers. To accelerate the solution process, a heuristic search algorithm is proposed to obtain (nearly) optimal solutions based on the characteristics of the model. The two subproblems are solved iteratively to improve the quality of solutions. A real-life case study in Chengdu, China, is performed to demonstrate the effectiveness and efficiency of the proposed model and algorithm.

scholarly journals A Short Turning Strategy for Train Scheduling Optimization in an Urban Rail Transit Line: The Case of Beijing Subway Line 4

2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Miao Zhang ◽  
Yihui Wang ◽  
Shuai Su ◽  
Tao Tang ◽  
Bin Ning
Keyword(s):  
Urban Traffic ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Rail Transit ◽  
Train Scheduling ◽  
Passenger Demand ◽  
Urban Rail ◽  
Train Services ◽  
Minlp Model ◽  
Beijing Subway

In urban rail transit systems, train scheduling plays an important role in improving the transport capacity to alleviate the urban traffic pressure of huge passenger demand and reducing the operation costs for operators. This paper considers the train scheduling with short turning strategy for an urban rail transit line with multiple depots. In addition, the utilization of trains is also taken into consideration. First, we develop a mixed integer nonlinear programming (MINLP) model for the train scheduling, where short turning train services and full-length train services are optimized based on the predefined headway obtained by the passenger demand analysis. The MINLP model is then transformed into a mixed integer linear programming (MILP) model according to several transformation properties. The resulting MILP problem can be solved efficiently by existing solvers, e.g., CPLEX. Two case studies with different scales are constructed to assess the performance of train schedules with the short turning strategy based on the data of Beijing Subway line 4. The simulation results show that the reduction of the utilization of trains is about 20.69%.

scholarly journals A Four-Type Decision-Variable MINLP Model for a Supply Chain Network Design

2010 ◽  
Vol 2010 ◽  
pp. 1-16 ◽  
Author(s):  
M. M. Monteiro ◽  
J. E. Leal ◽  
F. M. P. Raupp
Keyword(s):  
Supply Chain ◽  
Programming Model ◽  
Planning Horizon ◽  
Mixed Integer ◽  
Decision Variable ◽  
Abc Classification ◽  
Computational Implementation ◽  
Minlp Model ◽  
Nonlinear Programming Model ◽  
Outer Approximation Algorithm

We propose a mixed integer nonlinear programming model for the design of a one-period planning horizon supply chain with integrated and flexible decisions on location of plants and of warehouses, on levels of production and of inventory, and on transportation models, considering stochastic demand and the ABC classification for finished goods, which is an NP-hard industrial engineering optimization problem. Furthermore, computational implementation of the proposed model is presented through the direct application of the outer approximation algorithm on some randomly generated supply chain data.

scholarly journals Charging power optimisation for electric buses at terminals

2021 ◽  
Author(s):  
Bálint Csonka
Keyword(s):  
Public Transportation ◽  
Mixed Integer Linear Programming ◽  
Lower Number ◽  
Operating Costs ◽  
Mixed Integer ◽  
Charging Infrastructure ◽  
Total Cost ◽  
Network Characteristics ◽  
Bus Service ◽  
The Relationship

Charging infrastructure has a key role in the operation of electric buses in public transportation. In this paper, mixed-integer linear programming was used to model the bus service and capture the relationship among the network characteristics, vehicles, and charging unit attributes. The model supports the charging power optimisation at terminals to reduce the total operating costs of electric buses and charging units. The model was applied for the bus network of Kőbánya, Budapest. It was found that despite using more expensive high-power chargers, the total cost is lower because of the lower number of electric buses. It was also found that higher charging power does not affect the total cost significantly if it is higher than 350kW.

scholarly journals MINLP formulations for continuous piecewise linear function fitting

2021 ◽  
Author(s):  
Noam Goldberg ◽  
Steffen Rebennack ◽  
Youngdae Kim ◽  
Vitaliy Krasko ◽  
Sven Leyffer
Keyword(s):  
Linear Function ◽  
Piecewise Linear ◽  
Piecewise Linear Function ◽  
Mixed Integer ◽  
Function Fitting ◽  
Computational Performance ◽  
Integer Nonlinear Programming ◽  
Minlp Model ◽  
Necessary Constraints ◽  
Continuous Piecewise Linear Function

AbstractWe consider a nonconvex mixed-integer nonlinear programming (MINLP) model proposed by Goldberg et al. (Comput Optim Appl 58:523–541, 2014. 10.1007/s10589-014-9647-y) for piecewise linear function fitting. We show that this MINLP model is incomplete and can result in a piecewise linear curve that is not the graph of a function, because it misses a set of necessary constraints. We provide two counterexamples to illustrate this effect, and propose three alternative models that correct this behavior. We investigate the theoretical relationship between these models and evaluate their computational performance.

scholarly journals The Impact of Energy Storage along with the Allocation of RES on the Reduction of Energy Costs Using MILP

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3783
Author(s):  
Mateusz Andrychowicz
Keyword(s):  
Energy Storage ◽  
Mixed Integer Linear Programming ◽  
Distribution Systems ◽  
Operating Costs ◽  
Mixed Integer ◽  
Energy Costs ◽  
Power Exchange ◽  
Local Initiatives ◽  
One Year ◽  
The Impact

The paper shows a method of optimizing local initiatives in the energy sector, such as energy cooperatives and energy clusters. The aim of optimization is to determine the structure of generation sources and energy storage in order to minimize energy costs. The analysis is carried out for the time horizon of one year, with an hourly increment, taking into account various RES (wind turbines (WT), photovoltaic installations (PV), and biogas power plant (BG)) and loads (residential, commercial, and industrial). Generation sources and loads are characterized by generation/demand profiles in order to take into account their variability. The optimization was carried out taking into account the technical aspects of the operation of distribution systems, such as power flows and losses, voltage levels in nodes, and power exchange with the transmission system, and economic aspects, such as capital and fixed and variable operating costs. The method was calculated by sixteen simulation scenarios using Mixed-Integer Linear Programming (MILP).

scholarly journals SERVICE CATCHMENT OF MASS RAPID TRANSIT (MRT) FEEDER BUS: A PRELIMINARY STUDY OF T461 ROUTE TAMAN KAJANG UTAMA

2019 ◽  
Vol 17 ◽  
Author(s):  
Chloe Aida Lim Jhin Lin ◽  
Zakiah Ponrahono
Keyword(s):  
Data Collection ◽  
Urban Sprawl ◽  
Actual Data ◽  
Research Instrument ◽  
Bus Stop ◽  
Feeder Bus ◽  
Preliminary Study ◽  
Bus Service ◽  
The City ◽  
Rail Services

The planning and development of rail services require various considerations. Land availability, land use, catchment, route matching, infrastructure fitting, barrier free and micro-climate friendly designs are some of the factors heeded prior to such installations. A deviation between designated and highly demanded service area in urban sprawl zones of the city has been occurring in many Malaysian cities. These gaps have led to the mismatch between origin/destination of passengers and planned locations of train stations and its feeder bus stops. As such, rail services become less accessible to populations with the highest demands. This paper discusses the preliminary findings from a pilot study which seeks to calibrate the research instrument and validate preliminary findings before actual data collection for the purpose of determining the service catchment of the T461 feeder bus in Kajang MRT Station. The Garmin GPS device acts as the research instrument to obtain coordinates of locations where passengers board and alight feeder buses. On-board surveys and comparison analyses are methods that have been used to obtain the optimum GPS coordinates of the bus stop locations. The preliminary findings indicate that the research instrument is ready to be used for actual data collection and geospatial analysis to determine the service catchment of the T461 feeder bus service.

Impact of Automated Vehicles on Optimal Demand-Responsive Feeder Transit Network Design

2021 ◽  
Vol 2 (1) ◽  
pp. 84-100
Author(s):  
Amirreza Nickkar ◽  
Young-Jae Lee ◽  
Seyedehsan Dadvar
Keyword(s):  
Economic Benefits ◽  
Operating Costs ◽  
Transit Systems ◽  
Travel Costs ◽  
Bus Routing ◽  
Routing Optimization ◽  
Passenger Travel ◽  
Feeder Bus ◽  
Feeder Transit ◽  
Transit Network Design

This article aims to examine the economic benefits of automating flexible demand responsive feeder transit systems using a developed feeder bus routing optimization algorithm. The objective function of the algorithm is to minimize total passengers' and operating costs of the system. The results showed that when unit operating costs decline, total operating costs, and total costs obviously decline. Furthermore, when unit operating costs decline, the average passenger travel distance and total passenger travel costs decline while the ratio of total operating costs per unit operating costs increases. That means if unit operating costs decrease, the portion of passenger travel costs in the total costs increases, and the optimization process tends to reduce passenger costs more while reducing total costs. Assuming that automation of the vehicles reduces the operating costs, it will reduce not only total operating costs and total costs, but also total passenger travel costs.

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