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Title: Optimal Pricing in a Single Server System

We study optimal pricing in a single server queue when the customers valuation of service depends on their waiting time. In particular, we consider a very general model, where the customer valuations are random and are sampled from a distribution that depends on the queue length. The goal of the service provider is to set dynamic state dependent prices in order to maximize its revenue, while also managing congestion. We model the problem as a Markov decision process and present structural results on the optimal policy. We also present an algorithm to find an approximate optimal policy. We further present a myopic policy that is easy to evaluate and present bounds on its performance. We finally illustrate the quality of our approximate solution and the myopic solution using numerical simulations.

 
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Award ID(s):
2144316 2140534
NSF-PAR ID:
10516556
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
ACM
Date Published:
Journal Name:
ACM Transactions on Modeling and Performance Evaluation of Computing Systems
Volume:
8
Issue:
4
ISSN:
2376-3639
Page Range / eLocation ID:
1 to 32
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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