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.

scholarly journals Multiperiod Transfer Synchronization for Cross-Platform Transfer in an Urban Rail Transit System

Symmetry ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 1665
Author(s):  
Nan Cao ◽  
Tao Tang ◽  
Chunhai Gao
Keyword(s):  
Waiting Time ◽  
Transfer Problem ◽  
Urban Rail Transit ◽  
Mixed Integer ◽  
Rail Transit ◽  
Multiple Time ◽  
Transit System ◽  
Passenger Demand ◽  
Urban Rail ◽  
Cross Platform

Transfer synchronization is an important issue in timetable scheduling for an urban rail transit system, especially a cross-platform transfer. In this paper, we aim to optimize the performance of transfer throughout the daily operation of an urban rail transit system. The daily operation is divided into multiple time periods and each time period has a specific headway to fulfill time varied passenger demand. At the same time, the turn-back process of trains should also be considered for a real operation. Therefore, our work enhances the base of the transfer synchronization model taking into account time-dependent passenger demand and utilization of trains. A mixed integer programming model is developed to obtain an optimal timetable, providing a smooth transfer for cross-transfer platform and minimizing the transfer waiting time for all transfer passengers from different directions with consideration of timetable symmetry. By adjusting the departure time of trains based on a predetermined timetable, this transfer optimization model is solved through a genetic algorithm. The proposed model and algorithm are utilized for a real transfer problem in Beijing and the results demonstrate a significant reduction in transfer waiting time.

Study on the Scheduling Problem of Powder Painting Production - A Case Study

2010 ◽  
Vol 97-101 ◽  
pp. 2459-2464
Author(s):  
Zhang Yong Hu ◽  
Qiang Su ◽  
Jun Liu ◽  
Hai Xia Yang
Keyword(s):  
Large Scale ◽  
Production Efficiency ◽  
Production Performance ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Adaptive Search ◽  
Optimal Sequence ◽  
Integer Nonlinear Programming ◽  
Minlp Model

A large-scale powder-painting scheduling problem is explored. The purpose is to find out the optimal sequence of a number of batches that dynamically arrive from upstream processes within a given scheduling horizon. The objective is to enhance the production efficiency and decrease the production cost as well. To solve this problem, a mixed integer nonlinear programming (MINLP) model is constructed and an algorithm called greedy randomized adaptive search procedure (GRASP) is designed. Case studies demonstrate that the proposed approach can improve the production performance significantly.

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 Timetable Optimization of Rail Transit Loop Line with Transfer Coordination

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Rui-Jia Shi ◽  
Bao-Hua Mao ◽  
Yong Ding ◽  
Yun Bai ◽  
Yao Chen
Keyword(s):  
Waiting Time ◽  
Performance Indicators ◽  
Waiting Times ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit System ◽  
Urban Rail ◽  
Proposed Model ◽  
Timetable Optimization

In an urban rail transit system, it is important to coordinate the timetable of a loop line with its connecting lines so as to reduce the waiting time of passengers. This is particularly essential because transfer passengers usually account for the majority of the total passengers in loop lines. In this paper, a timetable optimization model is developed for loop line in order to minimize the average waiting time of access passengers and transfer passengers. This is performed by adjusting the headways and dwell times of trains on the loop line. A genetic algorithm is applied to solve the proposed model, and a numerical example is used to verify its effectiveness. Finally, a case study of a loop line in the Beijing urban rail transit system is conducted. Waiting times of the passengers and the number of waiting passengers are used as performance indicators to verify the optimization results in rush hours and non-rush hours. The results show that the average waiting times for the up-track and down-track are reduced by 3.69% and 2.89% during rush hours and by 11.60% and 11.47% during non-rush hours, respectively.

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.

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.

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