Fuzzy Random Continuous Review Inventory Model with Controllable Lead-Time and Exponential Crashing Cost

Abstract

AbstractIn this paper, a continuous review inventory model is studied in a mixed imprecise and uncertain environment. A methodology is proposed to quantify both imprecise (fuzzy) and stochastic (random) information simultaneously. This enables the simultaneous inclusion of both the inherent randomness present in any real-life inventory situation and the subjective evaluation of the decision maker into the model. A methodology is developed by assuming the annual customer demand to be a continuous fuzzy random variable following normal distribution with associated fuzzy probability density function. Also the lead-time is assumed to be a control parameter and a lead-time crashing cost, in the form of an exponential function, is incorporated into the total inventory cost. The optimal values of the decision variables are determined so that the crisp equivalent of total expected annual inventory cost is a minimum. Numerical analysis is presented to illustrate the proposed model and provide some insights.KeywordsInventoryContinuous reviewFuzzy random variableNormal distributionLead-time crashing cost