Fuzzy random Newsboy problem with chance distribution

Abstract

Due to increasing difficulty and challenging issues of newsboy problem under uncertainty, managers seek newer and appropriate approaches to apprehend more accurately the demand for perishable products and or the products having a short shelf life. This paper investigates a newsboy problem with fuzzy random demand in a single product business scenario. The classical newsboy model is extended to a fuzzy random newsboy problem to determine the optimal order quantity and expected profit under hybrid uncertainty. To solve the proposed model, a new solution approach based on chance constraint programming is proposed to formulate the crisp equivalent form of the fuzzy random newsboy model. Numerical examples and a real-life case study are presented to show the utility of the projected model. From the outcomes, decision makers can make comprehensive recommendations for the optimal order quantity and expected profit obtained by our proposed model under two-folded uncertainty. Also, a sensitivity analysis suggests that the profit and order quantity will increase (or decrease) with the increase (or decrease) of the mean demand.