Adjustable Robust Optimization Models for a Nonlinear Two-Period System

A. Takeda (), S. Taguchi and R. H. Tütüncü
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A. Takeda: Tokyo Institute of Technology
S. Taguchi: Toshiba Corporation
R. H. Tütüncü: Goldman Sachs Asset Management

Journal of Optimization Theory and Applications, 2008, vol. 136, issue 2, No 8, 275-295

Abstract: Abstract We study two-period nonlinear optimization problems whose parameters are uncertain. We assume that uncertain parameters are revealed in stages and model them using the adjustable robust optimization approach. For problems with polytopic uncertainty, we show that quasiconvexity of the optimal value function of certain subproblems is sufficient for the reducibility of the resulting robust optimization problem to a single-level deterministic problem. We relate this sufficient condition to the cone-quasiconvexity of the feasible set mapping for adjustable variables and present several examples and applications satisfying these conditions.

Keywords: Robust optimization; Two-period nonlinear optimization problem; Quasiconvex set valued map (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s10957-007-9288-8

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