scholarly journals Networked Timetable Stability Improvement Based on a Bilevel Optimization Programming Model

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Xuelei Meng ◽  
Bingmou Cui ◽  
Limin Jia ◽  
Yong Qin ◽  
Jie Xu
Keyword(s):  
Bilevel Programming ◽  
Programming Model ◽  
Bilevel Optimization ◽  
Particle Swarm Algorithm ◽  
Index Number ◽  
Train Timetable ◽  
Operating Rules ◽  
Buffer Time ◽  
The Status ◽  
Bilevel Programming Model

Train timetable stability is the possibility to recover the status of the trains to serve as arranged according to the original timetable when the trains are disturbed. To improve the train timetable stability from the network perspective, the bilevel programming model is constructed, in which the upper level programming is to optimize the timetable stability on the network level and the lower is to improve the timetable stability on the dispatching railway segments. Timetable stability on the network level is defined with the variances of the utilization coefficients of the section capacity and station capacity. Weights of stations and sections are decided by the capacity index number and the degrees. The lower level programming focuses on the buffer time distribution plan of the trains operating on the sections and stations, taking the operating rules of the trains as constraints. A novel particle swarm algorithm is proposed and designed for the bilevel programming model. The computing case proves the feasibility of the model and the efficiency of the algorithm. The method outlined in this paper can be embedded in the networked train operation dispatching system.

Emergency Logistics System Based on Bilevel Optimization Model

2013 ◽  
Vol 694-697 ◽  
pp. 3605-3609
Author(s):  
Bo Liu ◽  
Bo Li ◽  
Yan Li
Keyword(s):  
Genetic Algorithm ◽  
Bilevel Programming ◽  
Programming Model ◽  
Hybrid Genetic Algorithm ◽  
Optimal Solution ◽  
Bilevel Optimization ◽  
Logistics System ◽  
Emergency Logistics ◽  
Proposed Model ◽  
Bilevel Programming Model

A bilevel programming model is established to determine the emergency storage centers location and the resource supply plan of the provincial and municipal levels by the collaborative mode of the vertical supply and lateral transfer for the emergency logistics system in the unusual emergencies. And the optimal solution is obtained by the hybrid genetic algorithm. Finally, the case shows the effectiveness of the proposed model and its algorithm.

scholarly journals Optimizing Train Timetable Based on Departure Time Preference of Passengers for High-Speed Rails

2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Zhipeng Huang ◽  
Huimin Niu ◽  
Ruhu Gao ◽  
Haoyu Fan ◽  
Chenglin Liu
Keyword(s):  
Bilevel Programming ◽  
High Speed ◽  
Service Providers ◽  
Programming Model ◽  
Operating Cost ◽  
User Equilibrium ◽  
Optimal Operation ◽  
High Speed Railway ◽  
Train Timetable ◽  
Bilevel Programming Model

Passengers would like to choose the most suitable train based on their travel preferences, expenses, and train timetable in the high-speed railway corridor. Meanwhile, the railway department will constantly adjust the train timetable according to the distribution of passenger flows during a day to achieve the optimal operation cost and energy consumption saving plan. The question is how to meet the differential travel needs of passengers and achieve sustainable goals of service providers. Therefore, it is necessary to design a demand-oriented and environment-friendly high-speed railway timetable. This paper formulates the optimization of train timetable for a given high-speed railway corridor, which is based on the interests of both passengers and transportation department. In particular, a traveling time-space network with virtual departure arc is constructed to analyze generalized travel costs of passengers of each origin-destination (OD), and bilevel programming model is used to optimize the problem. The upper integer programming model regards the minimization of the operating cost, which is simplified to the minimum traveling time of total trains, as the goal. The lower level is a user equilibrium model which arranges each OD passenger flow to different trains. A general advanced metaheuristic algorithm embedded with the Frank–Wolfe method is designed to implement the bilevel programming model. Finally, a real-world numerical experiment is conducted to verify the effectiveness of both the model and the algorithm.

scholarly journals A Simultaneous Solution for Reserve Capacity Maximization and Delay Minimization Problems in Signalized Road Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Ozgur Baskan ◽  
Huseyin Ceylan ◽  
Cenk Ozan
Keyword(s):  
Bilevel Programming ◽  
Road Network ◽  
Programming Model ◽  
Numerical Test ◽  
User Equilibrium ◽  
Reserve Capacity ◽  
Delay Minimization ◽  
Weighted Sum Method ◽  
Capacity Maximization ◽  
Bilevel Programming Model

In this study, we present a bilevel programming model in which upper level is defined as a biobjective problem and the lower level is considered as a stochastic user equilibrium assignment problem. It is clear that the biobjective problem has two objectives: the first maximizes the reserve capacity whereas the second minimizes performance index of a road network. We use a weighted-sum method to determine the Pareto optimal solutions of the biobjective problem by applying normalization approach for making the objective functions dimensionless. Following, a differential evolution based heuristic solution algorithm is introduced to overcome the problem presented by use of biobjective bilevel programming model. The first numerical test is conducted on two-junction network in order to represent the effect of the weighting on the solution of combined reserve capacity maximization and delay minimization problem. Allsop & Charlesworth’s network, which is a widely preferred road network in the literature, is selected for the second numerical application in order to present the applicability of the proposed model on a medium-sized signalized road network. Results support authorities who should usually make a choice between two conflicting issues, namely, reserve capacity maximization and delay minimization.

Sign in / Sign up

Export Citation Format

Share Document