1982. Analysis and Optimization of a Hybrid Queueing System with Dynamic Pricing Strategies Based on Customer Ratings and Queue Length
Invited abstract in session WB-54: Stochastic Models and Optimization I, stream Stochastic modelling.
Wednesday, 10:30-12:00Room: Liberty 1.08
Authors (first author is the speaker)
| 1. | CHESOONG KIM
|
| Department of Business Administration, Sangji University |
Abstract
In this paper, we analyze and optimize a hybrid queueing system where arrival rates and service prices dynamically change based on customer ratings and queue length. The system combines features of multi-server and retrial queueing systems, proposing a pricing strategy that simultaneously considers customer satisfaction and system load. Specifically, higher customer ratings lead to increased arrival rates, while longer queue lengths result in higher service prices. A multi-dimensional Markov chain model is used to analyze the system's stability and calculate performance metrics. In addition, we derive optimal pricing policies to maximize service provider revenue and validates the proposed model's efficiency through numerical experiments under various scenarios. This work can contribute to enhancing the operational efficiency of various service systems where dynamic pricing is crucial, such as taxi networks and online delivery services.
Keywords
- Queuing Systems
- Optimization Modeling
- Stochastic Optimization
Status: accepted
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