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876. Stochastic Queuing-Based Optimization Problems for Network Design
Invited abstract in session TC-35: Stochastic Optimization with Decision-Dependent Uncertainty, stream Stochastic, Robust and Distributionally Robust Optimization.
Tuesday, 12:30-14:00Room: 44 (building: 303A)
Authors (first author is the speaker)
| 1. | Miguel Lejeune
|
| George Washington University |
Abstract
We study stochastic queueing-based optimization models to design networks in which the objective is to minimize the response time. The networks are modelled as collections of interdependent queueing systems in which the service times and the arrival of requests are random variables whose distribution parameters are determined endogenously. The optimization models take the form of nonconvex MINLP problems with fractional, exponential, and polynomial terms for which we propose a convex integer reformulation framework (MILP or convex MINLP).
Keywords
- Programming, Stochastic
- Programming, Nonlinear
- Queuing Systems
Status: accepted
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