期刊
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
卷 41, 期 10, 页码 1187-1200出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207720903171761
关键词
stochastic replenishment; chance constraint; fuzzy mixed-integer nonlinear programming; fuzzy simulation; simulated annealing; genetic algorithm; nonlinear programming; fuzzy nonlinear programming; inventory
While the usual assumptions in multi-periodic inventory control problems are that the orders are placed at the beginning of each period (periodic review) or depending on the inventory level they can happen at any time (continuous review), in this article, we relax these assumptions and assume that the periods between two replenishments of the products are independent and identically distributed random variables. Furthermore, assuming that the purchasing price are triangular fuzzy variables, the quantities of the orders are of integer-type and that there are space and service level constraints, total discount are considered to purchase products and a combination of back-order and lost-sales are taken into account for the shortages. We show that the model of this problem is a fuzzy mixed-integer nonlinear programming type and in order to solve it, a hybrid meta-heuristic intelligent algorithm is proposed. At the end, a numerical example is given to demonstrate the applicability of the proposed methodology and to compare its performance with one of the existing algorithms in real world inventory control problems.
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