Journal
COMPUTERS & OPERATIONS RESEARCH
Volume 103, Issue -, Pages 64-80Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2018.10.013
Keywords
Robust optimisation; Implementation uncertainty; Metaheuristics; Global optimisation
Categories
Funding
- EPSRC [EP/L504804/1, EP/M506369/1]
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We consider box-constrained robust optimisation problems with implementation uncertainty. In this setting, the solution that a decision maker wants to implement may become perturbed. The aim is to find a solution that optimises the worst possible performance over all possible perturbances. Previously, only few generic search methods have been developed for this setting. We introduce a new approach for a global search, based on placing a largest empty hypersphere. We do not assume any knowledge on the structure of the original objective function, making this approach also viable for simulation-optimisation settings. In computational experiments we demonstrate a strong performance of our approach in comparison with state-of-the-art methods, which makes it possible to solve even high-dimensional problems. (C) 2018 The Authors. Published by Elsevier Ltd.
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