Dynamic pricing of perishable products with random fuzzy demand

This paper considers a dynamic pricing problem for selling a given stock of a perishable product over a finite time horizon. We model the uncertain demand as random fuzzy variable and study the pricing problem in a random fuzzy environment. The retailer's dynamic pricing problem is formulated as three types of random fuzzy programming models-expected revenue maximization model, (α, β)-revenue maximization model and chance maximization model - to meet different goals. Random fuzzy simulations for some functions with random fuzzy parameters are given and embedded into genetic algorithm to design a hybrid intelligent algorithm. Numerical examples are also presented to illustrate the modeling idea and to show the effectiveness of the proposed algorithm.