Historically, congestion pricing is considered to be an efficient mechanism used to decrease total social cost by charging users' true costs including congestion externalities. Congestion pricing under uncertainty has been relatively little studied. In this paper, we review the literature on...

Deterministic congestion pricing has attracted most attentions in the literature. But little attention has been given to pricing under uncertainty, especially for heterogeneous commuters. In this paper, we investigate congestion externalities by considering commuters’ risk preferences and...

In this research, we consider an online assortment optimization problem, where a decision-maker needs to sequentially offer assortments to users instantaneously upon their arrivals and users select products from offered assortments according to the contextual multinomial logit choice model. We...

We propose a minimax concave penalized multi-armed bandit algorithm under generalized linear model (G-MCP-Bandit) for a decision-maker facing high-dimensional data in an online learning and decision-making process. We demonstrate that the G-MCP-Bandit algorithm asymptotically achieves the...