Risk-Adaptive Approaches to Stochastic Optimization: A Survey

arXiv:2212.00856v3 Announce Type: replace-cross
Abstract: Uncertainty is prevalent in engineering design, data-driven problems, and decision making broadly. Due to inherent risk-averseness and ambiguity about assumptions, it is common to address uncertainty by formulating and solving conservative optimization models expressed using measures of risk and related concepts. We survey the rapid development of risk measures over the last quarter century. From their beginning in financial engineering, we recount the spread to nearly all areas of engineering and applied mathematics. Solidly rooted …

abstract arxiv assumptions concepts cs.lg data data-driven decision decision making design development engineering engineering design making math.oc optimization risk stat.ml stochastic survey type uncertainty