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Event-driven and Attribute-driven Robustness
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M. Namakshenas *   , Mir Saman Pishvaee , M. Mahdavi Mazdeh |
| Iran University of Science and Technology , m_namakshenas@ind.iust.ac.ir |
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Abstract: (9614 Views) |
| Over five decades have passed since the first wave of robust optimization studies conducted by Soyster and Falk. It is outstanding that real-life applications of robust optimization are still swept aside; there is much more potential for investigating the exact nature of uncertainties to obtain intelligent robust models. For this purpose, in this study, we investigate a more refined description of the uncertain events including (1) event-driven and (2) attribute-driven. Classical methods transform convex programming classes of uncertainty sets. The structural properties of uncertain events are analyzed to obtain a more refined description of the uncertainty polytopes. Hence, tractable robust models with a decent degree of conservatism are introduced to avoid the over-protection induced by classical uncertainty sets. |
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| Keywords: Robust optimization, Convex optimization, Uncertainty sets, Uncertainty events |
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Full-Text [PDF 805 kb]
(17607 Downloads)
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Type of Study: Original |
Subject:
Production/Inventory
Received: 2018/04/3 | Accepted: 2018/04/3 | Published: 2018/04/3
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