Passenger-oriented optimization of lines in a mass transit system (original) (raw)

Design of urban public transport lines as a multiple criteria optimisation problem

Urban Transport XVI, 2010

The paper describes a mathematical programming approach used for the lineplanning problem in urban public transport. The input data include the transportation network in a city, O-D matrix of travel demand, and the set of available vehicles of specified transportation modes and types. The goal of line planning is to design the routes of lines and their frequencies. Supposing an initial set of lines has been proposed, the line-planning problem is formulated and solved as a multiple criteria optimisation problem, where the criteria reflect the travellers' demand for a high quality service, the operator's interest in an effective service, and the environmental impact of the vehicles. The solution to this problem specifies the number of vehicles of the given mode and type operating on the lines. Lines, which are not assigned a vehicle, will not operate. At the same time, the solution specifies optimal passenger routes in the line network. Then an iterative process follows which computes new line frequencies using a discrete choice model to respect passengers' behaviour when they have multiple travel alternatives.

Models for Line Planning in Public Transport

Lecture Notes in Economics and Mathematical Systems, 2008

The line planning problem is one of the fundamental problems in strategic planning of public and rail transport. It consists of finding lines and corresponding frequencies in a public transport network such that a given travel demand can be satisfied. There are (at least) two objectives. The transport company wishes to minimize its operating cost; the passengers request short travel times. We propose two new multicommodity flow models for line planning. Their main features, in comparison to existing models, are that the passenger paths can be freely routed and that the lines are generated dynamically.

Optimization Of The Urban Line Network Using A Mathematical Programming Approach

2012

The paper deals with the line-planning problem related to urban public transport. Given the transportation network in a city, the origin–destination matrix of travel demands, and the fl eet of available vehicles, the goal is to design the routes and frequencies of lines. The proposed solution method is a combination of the exact mathematical programming algorithm and a trip assignment procedure. The solution process consists of three stages: (i) initialization, (ii) designing the line network and setting the initial frequencies of selected lines, (iii) solution improvement. In the fi rst stage, an initial set of feasible lines is proposed. In the second stage, an optimal subset of candidate lines is selected and initial frequencies of lines are computed by solving a mathematical programming model of the line-planning problem. The problem is formulated as a multiple criteria optimization problem, where the criteria refl ect travelers’ demand for a high quality service, operator’s int...

A tool for the design of public transportation services

In this paper a model is described in order to determine the number of lines of a public transportation service, the layout of their lines amongst a set of candidates, their service capacity, and the resulting assignment of passengers to these facilities so as to minimize the total costs of the system. The model takes into account the delays for passengers that queue at the stations reflecting congestion effects of the transport service system and also, the abandonment of waiting queues at stations by passengers. Passengers are assumed to choose the lines they ride on by selecting the most convenient service line following a user equilibrium formulation.

Discrete optimization in public rail transport

Mathematical Programming, 1997

Many problems arising in traffic planning can be modelled and solved using discrete optimization. We will focus on recent developments which were applied to large scale real world instances.

Creation of Objective Functions for Transit Network Design

IFAC Proceedings Volumes, 1997

This paper describes the basic construction of the objective functions of the transit network design problem and proposes a new approach taking account of both passenger and operator interests. The approach presented combines the philosophy of the mathematical programming approaches with decision-making techniques, so as to allow the user to select from a number of alternatives. The nature of the overall formulation is nonlinear and mixed integer programming.

Service Oriented Line Planning and Timetabling for Passenger Trains

Researchers in mathematical optimization should grasp the currently available momentum and opportunities in the railway industry by not focusing too much on theoretical results, but by going for real-world applications of their models and techniques. The latter will lead to a win-win situation, both for the researchers and for the railway industry" Caprara et al.

Urban rail transit planning using a two-stage simulation-based optimization approach

In urban metro systems, stochastic disturbances occur repeatedly as a result of an increment of demands or travel time variations, therefore, improving the service quality and robustness through minimizing the passengers waiting time is a real challenge. To deal with dwell time variability, travel time and demand uncertainty, a two-stage GA-based simulation optimization approach is proposed in order to minimize the expected passenger waiting times. The proposed method here has the capability of generating robust timetables for a daily operation of a single-loop urban transit rail system. The first stage of the algorithm includes the evaluation of even-headway timetables through simulation experiments. In the second stage, the search space is limited to the uneven-headway patterns in such a manner where the algorithm keeps the average of headways close to the best evenheadway timetable, obtained from the first stage. The optimization is intended to adjust headways through simulation experiments. Computational experiments are conducted on Tehran Metropolitan Railway (IRAN) and the outcomes of optimized timetable obtained by this proposed method are demonstrated. This newly proposed two-stage search approach could achieve to a more efficient solution and speed up the algorithm convergence.

Joint Operating Revenue and Passenger Travel Cost Optimization in Urban Rail Transit

Journal of Advanced Transportation, 2018

Urban rail transit (URT) scheduling requires designing efficient timetables that can meet passengers’ expectations about the lower travel cost while attaining revenue management objectives of the train operators. This paper presents a biobjective timetable optimization model that seeks maximizing the operating revenue of the railway company while lowering passengers’ average travel cost. We apply a fuzzy multiobjective optimization and a nondominated sorting genetic algorithm II to solve the optimization problem and characterize the trade-off between the conflicting objective functions under different types of distances. To illustrate the model and solution methodology, the proposed model and solution algorithms are validated against train operation record from a URT line of Chengdu metro in China. The results show that significant improvements can be achieved in terms of the travel cost and revenue return criteria when implementing the solutions obtained by the proposed model.

An Analysis on Optimizing Full and Part Routes of Urban Rail Transit under Peak Times

Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019), 2019

The cross-section passenger flow of urban rail transit has a large difference in space during the peak times and the operation mode of full and part routes should be adopted. By analyzing the passenger flow in the peak times, aiming at the minimum cost of the enterprise and the passenger waiting time, the multi-objective optimization model can be constructed. By introducing the time value coefficient, the passenger waiting time will be converted into the cost of generalized waiting time. The multi-objective optimization mode is transformed into a single-objective optimization model. The genetic algorithm is used to solve this problem and calculates the frequency of trains. Finally, the validity of the model is verified by an example.