讲座简介：

• 主题1： Optimal timing for major transit investments under time-inconsistent preference

• Abstract: This paper addresses optimal major transit investment issues while considering time-inconsistent preference and population uncertainty. While the typical real option approach assumes that investors possess a constant discount rate over time, this paper proposes an extension of real option to model investors’ preference with a quasi-hyperbolic discount function. Two alternative assumptions about the strategies guiding the behavior of future investors are considered in this paper, namely naive authority and sophisticated authority. An optimal transit investment timing model is proposed that incorporates explicitly the effects of the investors’ forecast about their own future preferences. Analyses of the sensitivity of investment thresholds to transportation system parameters are conducted. The proposed model is illustrated in a Chinese city. Insightful findings are reported regarding the effect of time-inconsistency on optimal investment timing.

• 主题2： Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

• Abstract: The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.