A Method for Optimizing the Phased Development of Rail Transit Lines

Abstract

This paper develops a method for optimizing the construction phases for rail transit line extension projects with the objective of maximizing the net present worth and examines the economic feasibility of such extension projects under various financial constraints (i.e., unconstrained, revenue-constrained, and budget-constrained cases). A Simulated Annealing algorithm is used for solving this problem. Rail transit projects may be divided into several phases due to budget limits or demand growth that justifies different sections at different times. A mathematical model is developed to optimize these phases for a simple, one-route rail transit system, running from a Central Business District (CBD) to a suburban area. Some interesting results indicate that the economic feasibility of links with low demand is affected by the completion time of those links and their demand growth rate after their implementation. Sensitivity analysis explores the effects of interest rates on optimized results (i.e., construction phases and objective value). With further development, such a method should be useful to transportation planners and decision-makers in optimizing construction phases for rail transit line extension projects.

Open-source VRPLite Package for Vehicle Routing with Pickup and Delivery: A Path Finding Engine for Scheduled Transportation Systems

“…As shown in Fig. 1, Passenger 1 should be picked up from dummy node o 1 in time window [4,7] and dropped off at dummy node d 1 in time window [11,14], while Passenger 2 should be picked up from dummy node o 2 in time window [8,10] and dropped off at dummy node d 2 in time window [13,16]. Vehicle 1 also has High-speed train speed Train scheduling Zhou et al [22] Cumulative working hours in crew scheduling, cumulative running distance in electric multiple unit (EMU) maintenance scheduling…”

“…Both upper bound and lower bound of this problem are equal to 24, which increases by 4 compared to the optimal solution of the first example. Obviously, it is for the reason that the travel time of links (2, 3) and (4,5) and no extra vehicle or passenger waiting time is introduced.…”

“…When each transporting request is defined by determinate pickup and delivery points, the VRP becomes the vehicle routing problem with pickup and delivery (VRPPD). Practical applications of the VRPPD can be commonly found in urban rail transit management, to name a few, rail transit line planning [4,5], policy decision making [6,7], train operation management [8,9], train timetabling [10,11], and metro-based freight transportation [12]. In the emerging peer-to-peer ride-sharing service, a passenger can ask the driver to take him/her directly to the destination, and the passenger may also share this ride with one or more passengers.…”

Evolution of public transit modes in a commuter corridor

“…However, those methods were essentially static and incapable of revealing how the system service should be optimized in response to demand changes over an extended horizon. Cheng and Schonfeld (2015) presented a multi-period optimization model for the development of a rail transit line; nonetheless, the intermodal transfer was not considered. Problems such as how public transit modes should evolve with demand dynamics are still not fully solved.…”

“…Therefore, a static model is incapable of analyzing the evolution of modes. A multi-period model for extending the rail transit line is presented by Cheng and Schonfeld (2015). The implementation of a rail transit line is usually subdivided into several phases due to budget limits or insufficient demand.…”