Nilay Noyan, Gábor Rudolf, Optimization with Multivariate Conditional Value-at-Risk Constraints, Operations Research, Vol. 61, No. 4 (July-August 2013), pp. 990-1013 ...

We also compare direct MMSE optimization to optimization of several proxies to MMSE: Fisher information, maximum likelihood estimation error, and the Bayesian Cramér-Rao bound. We find that ...

We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...

With manual multivariable control, operators tend to keep the process farther from constraints and make moves less often, typically incurring an associated penalty in capacity, yield, energy, or ...

In this paper, a new constrained multivariable predictive control strategy based on T-S modeling approach and Particle Swarm Optimization is considered. The proposed method determines the control ...

ABSTRACT Recently, a new approach for optimization of conditional value-at-risk (CVAR) was suggested and tested with several applications. For continuous distributions, CVAR is defined as the expected ...

Multivariable predictive control technology increased oil and gas production by 4% from BP PLC's Marlin tension leg platform (TLP) in the Gulf of Mexico.

Combined with the robust optimization method, the stability of carbon emission constraints is verified under random disturbance scenarios (such as sensitivity analysis of different carbon emission ...