Improved rapid transit network design model: considering transfer effects

The rail rapid transit network design problem aims at locating train alignments and stations, maximizing demand coverage while competing with the current existing networks. We present a model formulation for computing tight bounds of the linear relaxation of the problem where transfers are also introduced. The number of transfers within a trip is a decisive attribute for attracting passengers: transferring is annoying and undesirable for passengers. We conduct computational experiments on different networks and show how we are able to solve more efficiently problems that have been already solved; sensitivity analysis on several model parameters are also performed so as to demonstrate the robustness of the new formulation

Improved rapid transit network design model: considering transfer effects

The rail rapid transit network design problem aims at locating train alignments and stations, maximizing demand coverage while competing with the current existing networks. We present a model formulation for computing tight bounds of the linear relaxation of the problem where transfers are also introduced. The number of transfers within a trip is a decisive attribute for attracting passengers: transferring is annoying and undesirable for passengers. We conduct computational experiments on different networks and show how we are able to solve more efficiently problems that have been already solved; sensitivity analysis on several model parameters are also performed so as to demonstrate the robustness of the new formulation

Combining robustness and recovery in rapid transit network design

When designing a transport network, decisions are made according to an expected value for network state variables, such as infrastructure and vehicle conditions, which are uncertain at a planning horizon of up to decades. Because disruptions, such as infrastructure breakdowns, will arise and affect the network on the day of operations, actions must be taken from the network design. Robust network designs may be implemented but they are extremely expensive if disruptions do not realise. In this paper, we propose a novel approach to the network design problem where robustness and recovery are combined. We look for the trade-off between efficiency and robustness accounting for the possibility of recovering from disruptions: recoverable robust network design. Computational experiments drawn from fictitious and realistic networks show how the presented approach reduces the price of robustness and recovery costs as compared to traditional robust and non-robust rapid transit network design approaches

Bilevel Optimization for On-Demand Multimodal Transit Systems

This study explores the design of an On-Demand Multimodal Transit System (ODMTS) that includes segmented mode switching models that decide whether potential riders adopt the new ODMTS or stay with their personal vehicles. It is motivated by the desire of transit agencies to design their network by taking into account both existing and latent demand, as quality of service improves. The paper presents a bilevel optimization where the leader problem designs the network and each rider has a follower problem to decide her best route through the ODMTS. The bilevel model is solved by a decomposition algorithm that combines traditional Benders cuts with combinatorial cuts to ensure the consistency of mode choices by the leader and follower problems. The approach is evaluated on a case study using historical data from Ann Arbor, Michigan, and a user choice model based on the income levels of the potential transit riders

An Integrated Methodology for the Rapid Transit Network Design

The Rapid Transit System Network Design Problem consists of two intertwined location problems: the determination of alignments and that of the stations. The underlying space, a network or a region of the plane, mainly depends on the place in which the system is being constructed, at grade or elevated, or underground, respectively. For solving the problem some relevant criteria, among them cost and future utilisation, are applied. Urban planners and engineering consulting usually select a small number of corridors to be combined and then analysed. The way of selecting and comparing these alternatives is performed by the application of the four-stage transit planning model. Due to the complexity of the overall problem, during last ten years some efforts have been dedicated to modelling some aspects as optimisation problems and to provide Operations Research methods for solving them. This approach leads to the consideration of a higher number of candidates than that of the classic corridor analysis. The main aim of this paper is to integrate the steps of the transit planning model (trip attraction and generation, trip distribution, mode choice and traffic equilibrium) into an optimisation process.Ministerio de Ciencia y Tecnología BFM2003-04062/MATEMinisterio de Fomento 2003/136

A short-turning policy for the management of demand disruptions in rapid transit systems

Rapid transit systems timetables are commonly designed to accommodate passenger demand in sections with the highest passenger load. However, disruptions frequently arise due to an increase in the demand, infrastructure incidences or as a consequence of fleet size reductions. All these circumstances give rise to unsupplied demand at certain stations, which generates passenger overloads in the available vehicles. The design of strategies that guarantee reasonable user waiting time with small increases of operation costs is now an important research topic. This paper proposes a tactical approach to determine optimal policies for dealing with such situations. Concretely, a short-turning strategy is analysed, where some vehicles perform short cycles in order to increase the frequency among certain stations of the lines and to equilibrate the train occupancy level. Turn-back points should be located and service offset should be determined with the objective of diminishing the passenger waiting time while preserving certain level of quality of service. Computational results and analysis for a real case study are provided.Junta de Andalucía P09-TEP-5022Natural Sciences and Engineering Research Council of Canada (NSERC) 39682-1

Joint Pricing, Operational Planning and Routing Design of a Fixed-Route Ride-sharing Service

Fixed-route ride-sharing services are becoming increasing popular among major metropolitan areas, e.g., Chariot, OurBus, Boxcar. Effective routing design and pricing and operational planning of these services are undeniably crucial in their profitability and survival. However, the effectiveness of existing approaches have been hindered by the accuracy in demand estimation. In this paper, we develop a demand model using the multinomial logit model. We also construct a nonlinear optimization model based on this demand model to jointly optimize price and operational decisions. Moreover, we develop a mixed integer linear optimization model to the routing design decision. And a genetic algorithm based approach is proposed to solve the optimization model. Two case studies based on a real world fixed-route ride-sharing service are presented to demonstrate how the proposed models are used to improve the profitability of the service respectively. We also show how this model can apply in settings where only limited public data are available to obtain effective estimation of demand and profit.Master of Science in EngineeringIndustrial and Systems Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/146788/1/49698122_Wanqing's Graduate Thesis (final).pdfDescription of 49698122_Wanqing's Graduate Thesis (final).pdf : Thesi