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A Largest Empty Hypersphere Metaheuristic for Robust Optimisation with Implementation Uncertainty

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>03/2019
<mark>Journal</mark>Computers and Operations Research
Volume103
Number of pages17
Pages (from-to)64-80
Publication statusPublished
Early online date17/10/18
Original languageEnglish

Abstract

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 of 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.