Traditional spectrum allocation policies may result in temporarily unused radio spectrum.
Cognitive radio (CR) has emerged as a promising technology to exploit the radio spectrum …

Robust optimization is an emerging area in research that allows addressing different
optimization problems and specifically industrial optimization problems where there is a …

In this paper we survey the primary research, both theoretical and applied, in the area of
robust optimization (RO). Our focus is on the computational attractiveness of RO …

This textbook provides a comprehensive modeling, reformulation and optimization approach
for solving production planning and related supply chain planning problems, covering topics …

The allocation of surgeries to operating rooms (ORs) is a challenging combinatorial
optimization problem. There is also significant uncertainty in the duration of surgical …

Robust counterpart optimization techniques for linear optimization and mixed integer linear
optimization problems are studied in this paper. Different uncertainty sets, including those …

Robust Optimization is a rapidly develo** methodology for handling optimization
problems affected by non-stochastic “uncertain-but-bounded” data perturbations. In this …

In this paper, we introduce an approach for constructing uncertainty sets for robust
optimization using new deviation measures for random variables termed the forward and …

We describe a two-stage robust optimization approach for solving network flow and design
problems with uncertain demand. In two-stage network optimization, one defers a subset of …

Traditional models of decision making under uncertainty assume perfect information, ie,
accurate values for the system parameters and specific probability distributions for the …