Stochastic optimization model for random demand stocks, with storage expenses accounting
Gheorghe Ciolan, Ion Preda, Mircea Năstăsoiu · MATEC Web of Conferences · 2017
The paper presents a possible stock level optimization method, based on a stochastic model. The consume demand for the stored product is considered a discrete random quantity. It was adopted the hypothesis that the repartition law of the demand probability is known for the time interval of stock existence (operation). The main aim of the optimization procedure is to minimize the total expenses (costs) involved by the existence or lack of the reserve stock. For a better understanding of the proposed algorithm, a calculation example is presented.