Neutrosophic Vision of the Expected Opportunity Loss Criterion (NEOL) Decision Making Under Risk

Abstract

One of the major challenges facing decision-makers at the present time is obtaining complete 
information about the issue under study, due to the unstable conditions of the work 
environment that are beyond the control of decision-makers, which requires them to reach an 
optimal decision in light of these circumstances and fluctuations and to benefit from the data 
that is collected. Collected by specialists to determine the appropriate probability distribution 
corresponding to random cases of nature, here we are faced with the issue of making a 
decision in the event of risk because the probability distribution is a distribution linked to the 
data controlled by the conditions of the work environment, which entails a great risk. 
Decision makers bear the responsibility of choosing the optimal decision that reduces This 
risk is achieved and the greatest possible profit and the least possible loss are achieved. The 
issue of decision-making becomes more complex as the number of events increases, and we 
are in dire need of an ideal study of the issue that takes into account all the circumstances of 
the work environment. The concept of missed opportunity is very useful in analyzing the 
decision making under risk, after making the decision and the occurrence of events, the 
decision makers may regret and wish they had chosen actions different from those they chose 
at the beginning. To reduce the regret of the decision makers and minimize the expected lost 
opportunity, researchers in the field of classical operations research presented the criterion 
of the expected lost opportunity through which the decision can be determined. The ideal 
with the least percentage of regret. In this research, we present a neutrosophic vision of the 
expected opportunity loss criterion by taking the data of the issue under study. neutrosophic 
values are ranges whose lowest limit expresses profit in the worst conditions, and only the 
highest represents profit in the best conditions. 

DOI: 10.5281/zenodo.10795630