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Event-driven and Attribute-driven Robustness
M. Namakshenas Mr. , Mir Saman Pishvaee Dr., M. Mahdavi Mazdeh Dr.
Iran University of Science and Technology , m_namakshenas@ind.iust.ac.ir
Abstract:   (123 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.
Keywords: Robust optimization, Convex optimization, Uncertainty sets, Uncertainty events
Full-Text [PDF 803 kb]   (30 Downloads)    
Type of Study: Original | Subject: Production/Inventory
Received: 2018/04/3 | Accepted: 2018/04/3 | Published: 2018/04/3
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مجله انجمن ایرانی تحقیق در عملیات Iranian Journal of Operations Research
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