Supply chain coordination: an inventory model for single-period utility product under fuzzy demand

Abstract

Traditionally, the classical and well-known stochastic newsboy (or news vendor) models were used to solve the uncertainty issues for single-period utility products. These models focused on the randomness aspect of uncertainty and were developed using probability theory. Nevertheless, historical data is not always available and reliable for estimating demand probabilities for single-period utility products. In this paper, we consider an integrated decision model for a distributor and a retailer to determine the optimal delivered quantities of a single-period utility product from warehouses to retailing sites with fuzzy demands to maximize the overall profit. A genetic algorithm with a dynamically adaptive penalty function is designed to solve the model. An example of the crisp demand case is also included in the study for comparison. From the analysis of the illustrated example, we find that the percentage of the price shared by the distributor influences the profit allocation significantly and should be carefully considered in the negotiation between the two parties.