Recently, a new approach for optimization of Conditional Value-at-Risk (CVaR) was suggested
and tested with several applications. For continuous distributions, CVaR is defined as the …

The paper considers modelling of risk-averse preferences in stochastic programming problems
using risk measures. We utilize the axiomatic foundation of coherent risk measures and …

Recently, a new approach for optimization of Conditional Value-at-Risk (CVaR) was suggested
and tested with several applications. By definition, CVaR, also called Mean Excess Loss, …

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 …

This paper surveys the most recent advances in the context of decision making under
uncertainty, with an emphasis on the modeling of risk-averse preferences using the apparatus of …

29.1 Introduction This paper applies risk management methodologies to the optimization of
a portfolio of hedge funds (fund of funds). We compare risk management techniques based …

In this paper, a branch-and-bound algorithm for finding all cliques of size k in a k-partite
graph is proposed that improves upon the method of Grunert et al. (in Comput Oper Res 29(1):13…

We consider the problem of detecting temporal changes in the functional state of human
subjects due to varying levels of cognitive load using real-time psychophysiological data. The …

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 …

We study a framework for constructing coherent and convex measures of risk that is inspired
by infimal convolution operator, and which is shown to constitute a new general …