Optimization of Inventory Level Using Fuzzy Probabilistic Exponential Two Parameters Model

Inventory control is an important factor in trading activities. Inventory control aims to ensure product availability. Several factors affect the level of inventory including the level of demand factor, maximum inventory, and the level of deterioration. If the influencing factors cannot be defined with certainty and follow a certain statistic distribution then the fuzzy probabilistic approach can be applied. This research discusses the problem of optimizing the inventory of red chillies at the retail level. The level of deterioration is assumed to follow an exponential distribution and demand follows a Pareto distribution. Statistical parameters are estimated using the Maximum likelihood method and cost parameters are expressed by triangular fuzzy numbers. Based on the calculation results for several beta values, the highest total cost is 405143.6 rupiah, a maximum inventory level of 15 kg, and an order cycle time of 0.923 days

On a correspondence between probabilistic and fuzzy choice functions

Probabilistic and fuzzy choice functions are used to describe decision situations in which some degree of uncertainty or imprecision is involved. We propose a way to equate these two formalisms by means of residual implication operations. Furthermore, a set of new rationality conditions for probabilistic choice functions is proposed and proved to be sufficient to ensure that the associated fuzzy choice function is rational