Adaptive discretization-based algorithms for semi-infinite programs with unbounded variables
نویسندگان
چکیده
Abstract The proof of convergence adaptive discretization-based algorithms for semi-infinite programs (SIPs) usually relies on compact host sets the upper- and lower-level variables. This assumption is violated in some applications, we show that indeed problems can arise when are applied to SIPs with unbounded To mitigate these problems, first examine underlying assumptions algorithms. We do this paradigmatically using lower-bounding procedure Mitsos [Optimization 60(10–11):1291–1308, 2011], which uses algorithm proposed by Blankenship Falk [J Optim Theory Appl 19(2):261–281, 1976]. It noteworthy considered essentially same broad class give sharper, slightly relaxed, achieve guarantees. guarantees also hold certain variables based sharpened assumptions. However, may be difficult prove a priori. For cases, propose additional, stricter, might easier imply Using additional assumptions, present numerical case studies Finally, review applications tractable
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ژورنال
عنوان ژورنال: Mathematical Methods of Operations Research
سال: 2022
ISSN: ['0042-0573', '1432-5217', '1432-2994']
DOI: https://doi.org/10.1007/s00186-022-00792-y