作者：Hosseini, Mojtaba; Turner, John
作者单位：University of Iowa; University of California System; University of California Irvine
摘要：Since its inception, Benders decomposition (BD) has been successfully applied to a wide range of large-scale mixed-integer (linear) problems. The key element of BD is the derivation of Benders cuts, which are often not unique. In this paper, we introduce a novel unifying Benders cut selection technique based on a geometric interpretation of cut depth, produce deepest Benders cuts based on & ell;p-norms, and study their properties. Specifically, we show that deepest cuts resolve infeasibility t...
作者：Baucells, Manel; Zorc, Sasa
作者单位：University of Virginia
摘要：The classic sequential search problem rewards the decision maker with the highest sampled value minus a cost per sample. If the sampling distribution is unknown, then a Bayesian decision maker faces a complex balance between exploration and exploitation. We solve the stopping problem of sampling from a normal distribution with unknown mean and variance and a conjugate prior, a longstanding open problem. The optimal stopping region may be empty (it may be optimal to continue the search regardle...
