found: Work cat.: King, A.J. Issues in risk modeling for multi-stage systems, 1997:abstr. (Key words: robust optimization) p. 3 (we show that the second-stage decisions of robust optimization may not be optimal and suggest a mathematical formulation that enforces optimality)
found: Mathematical programming glossary, via WWW, Aug. 11, 2006(Robust optimization. A term given to an approach to deal with uncertainty, similar to the recourse model of stochastic programming, except that feasibility for all possible realizations (called scenarios) is replaced by a penalty in the objective, As such, the approach integrates goal programming with a scenario-based description of problem data)
found: Yin, Y. Developing optimal planning and management strategies for a robust highway system, 2005:p. vii (Robust optimization is a modeling methodology to solve optimization problems in which the data are uncertain and only known to belong to some uncertainty set. The approach is to seek optimal (or near optimal) solutions that are not overly sensitive to any realization of uncertainty)
found: Takeda, A. Adjustable robust optimization models for nonlinear multi-period optimization, via WWW, Aug. 11, 2006(Robust optimization (RO) is a term that is used to describe both modeling strategies and solution methods for optimization problems that are defined by uncertain inputs. The objective of robust optimization models and algorithms is to obtain solutions that are guaranteed to perform well (in terms of feasibility and near-optimality) for all, or at least most, possible realizations of the uncertain input parameters)
notfound: MathWorld, via WWW, Aug. 11, 2006;Glossary of mathematical terms, via WWW, Aug. 11, 2006
