Continuous review reorder point problems in a fuzzy environment

In traditional continuous review reorder point problems, probability theory has been wildly explored to deal with uncertain cases. In most situations, the decision maker is assumed to be aware of the probability distribution of uncertainty when the probability theory is applied. However, this is seldom the case. In the most situations, the uncertainty is estimated within a certain interval without any knowledge of the probability distribution within the interval. In this investigation, the application of fuzzy sets theory is introduced for continuous review reorder point problems. It is assumed that uncertainties may appear in the demand over the lead time and in holding costs where decisionmaking is characterised by the lack of precise future estimates of the uncertain information. The minimised possible total cost is obtained by a corresponding reorder point and quantity. The computational aspect of the fuzzy model and its interpretations are illustrated by examples. Finally, deterministic approximations to this fuzzy approach are also investigated.