Khaled Alkhaledi

Newsvendor revisited: risk premiums of loss aversion

ABSTRACT The classical newsvendor model in economics and decision theory treats losses and gains equally likely. However, decision makers are usually loss-averse as probable losses have more impact on humans than probable gains. This study presents a new variant of the newsvendor problem of loss-averse decision makers. The optimal order quantity is found by maximizing the expected utility of bounded functions. The implications of loss aversion on the certainty equivalents and risk premiums were also analyzed. Two case studies of exponential utility and normal demand were considered. A new elegant form of the optimal order quantity is established. The results show that when exponential loss aversion exists, the newsvendor optimal quantity serves as a lower(upper) bound on the optimal quantities. Moreover, high loss aversion entails higher RP. Similar findings hold by increasing the overage/underage costs and the demand standard deviation. Possible future extensions are demonstrated at the end of the paper.

Platelets inventory management: A rolling horizon Sim–Opt approach for an age-differentiated demand

ABSTRACT Platelets are highly perishable components of blood. The shelf life of platelets is very short during which the platelets should be transfused, otherwise spoiled. It is evident that some medical conditions require platelets of specific ages. In this study, a stocking model of platelets is considered under age-differentiated and stochastic demand. The model aims at finding the optimal quantities by minimising the overall inventory costs. A hybrid of simulation and optimisation is established to optimise the decision variables. This work contributes to the existing literature by discriminating platelets by five ages, employing a new inventory policy of a rolling demand, and using simulation-optimisation framework. Shelf lives of 3 and 4 days were considered for the comparison with literature. The proposed model could outperform the selected policies by demonstrating lower costs. Moreover, the model resulted in lower cost per platelets’ unit compared to the actual costs of some selected hospitals.

A study on the use of propane (R-290) in vending machines as a substitute for R-134a to minimise the global warming potential

The refrigerant R-134a is widely used in vending machines, and it is a greenhouse gas with high global warming potential. The United States Environmental Protection Agency has mandated that R-134a be replaced with an environmentally friendly refrigerant. In this study, we compared the performance and safety of R-290 as a substitute for R-134a in vending machines. We compared the two refrigerants in a vending machine equipped with a single-stage compressor, four thermocouples, and a data log recorder. Our results demonstrate that R-290 performs as well as R-134a; in addition, it uses 31.4% less energy and 60% less refrigerant. The evaporator and condenser temperatures for R-290 were comparable to those for R-134a. Therefore, we conclude that R-290 is an excellent replacement for R-134a. In addition, R-134as global warming potential is 1300, while R-290s global warming potential is 3, and its ozone depletion potential is zero. Finally, R-290 can be used safely and complies with Underwriter Laboratory® safety standards.

A stochastic non-expected utility for modelling human errors of certainty equivalents

When a decision maker encounters a decision making problem of uncertain outcomes, he/she tends to estimate the so called certainty equivalent of the anticipated rewards, which resembles the benefit measure per unit increase in the expected payoff. Such certainty estimation results in underestimation and sometimes overestimation of the possible rewards. Hence, when two decision problems of uncertain outcomes are to be compared, the decision maker may unintentionally prefer one alternative over another due to the risk imposed by the uncertainty of the outcomes, while in reality the best choice is the other way around. In this paper, we present a model to resolve the complications of overestimation/underestimation of an individuals certainty equivalent by introducing a stochastic non-excepted utility model that adds an error component to the estimated certainty equivalent by the decision maker. The error distribution is optimised via training datasets. By stochastic representation of the expected utility and its corresponding certainty equivalent, we can resolve the decision making situations when the decision maker is risk averse/seeker. To demonstrate the merits of the presented model, different datasets are tested; the model shows a remarkable prediction capability of human choices under risk and uncertainty.