Robustifying against Event-driven and Attribute-driven Uncertainties
محل انتشار: سیزدهمین کنفرانس بین المللی مهندسی صنایع
سال انتشار: 1395
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 545
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شناسه ملی سند علمی:
IIEC13_299
تاریخ نمایه سازی: 14 شهریور 1396
چکیده مقاله:
Over five decades have passed since the first wave of robustoptimization studies conducted by Soyster [1] and Falk [2].It is outstanding that real-life applications of robustoptimization are still swept aside; there is much morepotential for investigating the exact nature of uncertaintiesto have intelligent robust models. For this purpose, in thisstudy, we investigate a more refined description of theuncertain events including (1) Event-driven and (2)Attribute-driven. Instead of model-based calibration ofrobustness, we analyze the structural properties of uncertainevents to obtain a more refined description of the uncertaintypolytopes. Hence, we introduce tractable robust models witha decent degree of conservatism and aversion from overprotectioncaused by the classic cardinality-restricteduncertainty polytopes.
کلیدواژه ها:
نویسندگان
Mohammad Namakshenas
chool of Industrial Engineering Iran University of Science and Technology, Tehran, Iran
Mir Saman Pishvaee
School of Industrial Engineering Iran University of Science and Technology, Tehran, Iran
Mohammad Mahdavi mazdeh
School of Industrial Engineering Iran University of Science and Technology, Tehran, Iran