Various types of uncertainties and imprecision are inherent in real in
ventory problems. They are classically modeled using the approaches fr
om the probability theory. However, there are uncertainties that canno
t be appropriately treated by usual probabilistic models. The question
s how to define inventory optimization tasks in such environment and h
ow to interpret optimal solutions arise.This paper considers the modif
ication of EOQ formula in the presence of imprecisely estimated parame
ters. For example, holding and ordering costs are often not precisely
known and are usually expressed by linguistic terms such as: ''Holding
cost is approximately of value c(h) '', or: ''Ordering cost is about
value c(0) or more''. These imprecise parameters are presented by fuzz
y numbers, defined on a bounded interval on the axis of real numbers.
Alternative approaches to determining the optimal order quantity in a
fuzzy environment are developed, illustrated by a selection of example
s, and discussed.