Two-Stage Stochastic Programming Model for Robust Personal Rapid Transit Network Design

Abstract

This study investigated the personal rapid transit (PRT) guideway network design problem at a strategic level. PRT is known as an on-demand mobility method serving the first or last mile of travel demand, which can fluctuate significantly during a day. This on-demand property may make the system vulnerable to changes in the pattern of demand. The robustness of the PRT guideway network refers to the capability to fit different demand patterns. The motivation of this study was to take the uncertainty of demand into consideration in the process of network design to enhance the robustness of the PRT guideway network in operation. This problem was formulated as a two-stage stochastic linear programming model. The model was applied to a case study with real travel demand data from Singapore. The results of the comparison study show that the network designed via the proposed model is robust and cost-effective.