Analysis of random instances of optimization problems provides valuable insights into the behavior and properties of problem's solutions, feasible region, and optimal values, especially in large-scale cases. A class of problems that have been studied extensively in the literature using the...

This paper applies formal risk management methodologies to optimization of a portfolio of hedge funds (fund of funds). We compare recently developed risk management methodologies: Conditional Value-at-Risk and Conditional Drawdown-at-Risk with more established Mean-Absolute Deviation, Maximum...

The paper considers solving of linear programming problems with p-order conic constraints that are related to a certain class of stochastic optimization models with risk objective or constraints. The proposed approach is based on construction of polyhedral approximations for p-order cones, and...