scholarly journals Gaussian Process State-Space Models with Time-Varying Parameters and Inducing Points

2021 ◽  
Author(s):  
Yuhao Liu ◽  
Petar M. Djuric
Keyword(s):  
Gaussian Process ◽  
State Space ◽  
State Space Models ◽  
Time Varying ◽  
Varying Parameters ◽  
Time Varying Parameters

APPROXIMATE DYNAMIC PROGRAMMING TECHNIQUES FOR THE CONTROL OF TIME-VARYING QUEUING SYSTEMS APPLIED TO CALL CENTERS WITH ABANDONMENTS AND RETRIALS

2009 ◽  
Vol 24 (1) ◽  
pp. 27-45 ◽  
Author(s):  
Dennis Roubos ◽  
Sandjai Bhulai
Keyword(s):  
Dynamic Programming ◽  
State Space ◽  
Approximate Dynamic Programming ◽  
Retrial Queue ◽  
The State ◽  
Space Representation ◽  
Time Varying ◽  
Queuing Systems ◽  
Varying Parameters ◽  
Time Varying Parameters

In this article we develop techniques for applying Approximate Dynamic Programming (ADP) to the control of time-varying queuing systems. First, we show that the classical state space representation in queuing systems leads to approximations that can be significantly improved by increasing the dimensionality of the state space by state disaggregation. Second, we deal with time-varying parameters by adding them to the state space with an ADP parameterization. We demonstrate these techniques for the optimal admission control in a retrial queue with abandonments and time-varying parameters. The numerical experiments show that our techniques have near to optimal performance.

Sign in / Sign up

Export Citation Format

Share Document