Browsing by Subject "Dynamic risk measures"

Now showing 1 - 3 of 3

Open Access
Optimal timing of living-donor liver transplantation under risk-aversion
(2016-07) Köse, Ümit Emre
Liver transplantation, which can be performed from either living-donors or cadavers, is the only viable treatment for end-stage liver diseases. In this study, we focus on living-donor liver transplantation. The timing of the transplantation from a living-donor is crucial as it affects the quality and the length of the patient's lifetime. The studies in the literature use risk-neutral Markov decision processes (MDPs) to optimize the timing of transplantation. However, in real life, the patients and the physicians are usually risk-averse, therefore, those risk neutral models fail to represent the real behavior. In this study, we model the living-donor liver transplantation problem as a risk-averse MDP. We incorporate risk-aversion into the MDP model using dynamic coherent measures of risk, and in order to be able to re ect varying risk preferences of the decision makers, we use first-order mean-semi-deviation and mean-AVaR as the one-step conditional measures of risk. We obtain optimal policies for patients having cirrhotic diseases or hepatitis B under different risk preferences and organs of different quality. We also measure the sensitivity of the optimal policies to the transition probabilities and to the quality of life. We further perform a simulation study in order to find the distribution of lifetime under the risk-averse optimal policies.
Open Access
Risk-averse control of undiscounted transient Markov models
(Society for Industrial and Applied Mathematics, 2014) Çavuş, Ö.; Ruszczyński, A.
We use Markov risk measures to formulate a risk-averse version of the undiscounted total cost problem for a transient controlled Markov process. Using the new concept of a multikernel, we derive conditions for a system to be risk transient, that is, to have finite risk over an infinite time horizon. We derive risk-averse dynamic programming equations satisfied by the optimal policy and we describe methods for solving these equations. We illustrate the results on an optimal stopping problem and an organ transplantation problem.
Open Access
Risk-averse optimization of wind-based electricity generation with battery storage
(2022-12) Eser, Merve
As the global installed capacity of wind power increases, various solutions have been developed to accommodate the intermittent nature of wind. Investing in battery storage reduces power fluctuations, improves the reliability of delivering power on demand, and decreases wind curtailment. In the literature, power producers are generally modelled as risk-neutral decision makers, and the focus has been on expected profit maximization. For many privately-held small independent power producers, it is more important to capture their risk-aversion through specialized risk measurements driven by the owners’ specific risk preferences, even though the expected value-maximization objective is very desirable for large corporations with diversified investors. We consider a risk-averse, privately-held, small Independent Power Producer interested in investing in a battery storage system and jointly operating the wind farm and storage system with a trans-mission line connected to the market. We formulate the problem as a Markov decision process (MDP) to find optimal investment, generation, and operational storage decisions. Using dynamic coherent risk measures, we incorporate risk-aversion into our formulation. By choosing the risk measure as first-order mean semi-deviation, we obtain optimal threshold-based policy structure as well as optimal storage investment capacity. We perform a sensitivity analysis on optimal storage capacity with respect to the risk-aversion degree and transmission line limitations.