Risk-Adaptive Approaches to Stochastic Optimization: A Survey

Understand

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.