Wake steering optimization under uncertainty

Optimization under Uncertainty Optimization Under Uncertainty: An Overview

Optimization under Uncertainty Optimization under Uncertainty: An Overview Urmila Diwekar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Two-Stage Stochastic Linear Programming: A Tutorial Vicente Rico-Ramirez . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Combinatorial Optimization under Uncertainty Ki-Joo Kim . . . . . . . . . . . . . . . . . . . . . . . . . . ...

Optimization Under Uncertainty

Most optimization problems in real life do not have accurate estimates of the problem parameters at the optimization phase. Stochastic optimization models have been studied widely in the literature to address this problem. The expected value optimization is reasonable in a repeated decision making framework. However, it does not sufficiently guard against the worst case future in more risk aver...

Routing Optimization Under Uncertainty

We consider a class of routing optimization problems under uncertainty in which all decisions are made before the uncertainty is realized. The objective is to obtain optimal routing solutions that would, as much as possible, adhere to a set of specified requirements after the uncertainty is realized. These problems include finding an optimal routing solution to meet the soft time window require...

Optimization under Uncertainty

Robustness-based portfolio optimization under epistemic uncertainty

In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...