Random variables that stand for cost, loss or damage must be confronted in numerous
situations. Dealing with them systematically for purposes in risk management, optimization …

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 …

In this paper we address the problem of decision making within a Markov decision process
(MDP) framework where risk and modeling errors are taken into account. Our approach is to …

The present study assesses supply chain resilience based on network structural parameters.
Resilience is computed as a composite effect of density, centrality, connectivity, and network …

From the mathematical perspective considered in this tutorial, risk management is a
procedure for shaping a risk distribution. Popular functions managing risk are value-at-risk …

General deviation measures are introduced and studied systematically for their potential
applications to risk management in areas like portfolio optimization and engineering. Such …

Decisions often need to be made before all the facts are in. A facility must be built to
withstand storms, floods, or earthquakes of magnitudes that can only be guessed from …

Portfolio analysis and optimization, together with the associated risk assessment and
management, require knowledge of the likely distributions of returns at different time scales …

This book presents sound principles and useful methods for making investment and risk
management decisions in the presence of hedgeable and nonhedgeable risks. In everyday …

Diversification is one of the major components of investment decision-making under risk or
uncertainty. However, paradoxically, as the 2007–2009 financial crisis revealed, the concept …