Abstract
This paper investigates a group of computing schemas for economic order quantity as fuzzy values, and the corresponding optimal stock quantity of the invenyory with backorder. We express the fuzzy order quantity as the normal triangular fuzzy number ( q 1, q 0, q 2), and then we solve the aforementioned optimization problem under the constraints 0 < s ⩽ q 1 < q 0 < q 2, where s denotes the optimizing stock quantity. We find that, after defuzzification, the total cost is slightly higher than in the crisp model; however, it permits better use of the economic fuzzy quantities arising with changes in orders, deliveries, and sales.
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