Real-Time Dynamic Pricing for Revenue Management with Reusable Resources, Advance Reservation, and Deterministic Service Time Requirements

Abstract

In “Real-Time Dynamic Pricing for Revenue Management with Reusable Resources, Advance Reservation, and Deterministic Service Time Requirements,” Lei and Jasin consider a fundamental dynamic pricing problem when resources are reusable. In this problem, demand arrives according to a price-sensitive nonstationary rate, requesting a service that uses a combination of different types of resources for a deterministic duration of time. The resources are reusable in the sense that they can be immediately used to serve a new customer on the completion of the previous service. Moreover, different customers may have different service time requirement and may book the service in advance. The objective is to construct a dynamic pricing control that maximizes expected total revenues. They develop real-time heuristic controls based on the solution of the deterministic relaxation of the original stochastic problem and show that the proposed controls are near optimal in the regime of large demand and large resource capacity.

Real-Time Spatial–Intertemporal Pricing and Relocation in a Ride-Hailing Network: Near-Optimal Policies and the Value of Dynamic Pricing

“…The second literature studies revenue management problems in which finite resources can be repeatedly used to serve arriving demands after the completion of service time. Recent works have studied such problems in the context of capacity planning (Besbes et al 2021a), admission control Radovanovic 2010, Chen et al 2017), pricing control , Besbes et al 2019, Lei and Jasin 2020, and assortment control (Owen and Simchi-Levi 2018, Feng et al 2019, Gong et al 2019, Rusmevichientong et al 2020. The major difference between our paper and the aforementioned works is that we consider a problem where resources are moving in a network, and the location of a resource unit in the network changes upon the completion of service.…”

“…Finally, our work is also related to the stream of literature on real-time dynamic pricing and the literature on revenue management with reusable resources. The former literature seeks to find computationally efficient dynamic pricing controls that can be implemented in real-time (i.e., without having to resort to large-scale re-optimizations) and have provably near-optimal performances; see e.g., Jasin (2014), Chen et al (2015), Lei et al (2018), and Lei and Jasin (2020). The second literature studies revenue management problems in which finite resources can be repeatedly used to serve arriving demands after the completion of service time.…”

The Power of Static Pricing for Reusable Resources

“…Multi-resource: Paschalidis and Liu (2002) extend the asymptotic optimality of static pricing in Paschalidis and Tsitsiklis (2000) to the case of multiple resources and incorporate potential demand substitution effects. Lei and Jasin (2020) consider the problem of pricing reusable resources with deterministic service times and derives heuristic policies that are asymptotically optimal. Doan et al (2020) consider a case with ambiguous demand and service time distributions and efficiently construct fixed-price policies.…”

Static Pricing: Universal Guarantees for Reusable Resources

“…Various related studies focus on dynamic heuristics, multiple types of reusable resources, and other levers beyond pricing. Lei and Jasin (2018) studies the dynamic pricing problem in a setting with deterministic service times and describe policies that are asymptotically optimal in the regime where demand and resource capacity are both large. Variants of the assortment optimization problem have been considered in Rusmevichientong, Sumida, and Topaloglu (2017), Owen and Simchi-Levi (2017) and Goyal, Iyengar, and Wang (2018) with various universal approximation guarantees.…”