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Abstract

The purpose of this study is to minimize the present value of the joint expected total costs in an inventory model considering a fuzzy interest rate. In recent years, inventory policies have played a critical role in supply chain management in highly competitive environments. Therefore, this study aims at determining a suitable inventory policy to enhance the benefits of the supply chain. Reducing lead times and the associated inventory costs are vital concerns in supply chain management. However, most previous studies have not considered the effect of a time value. In addition, this study develops an integrated inventory model that considers crashing costs and time values to reduce inventory problems. In addition, this study applies a signed distance, a ranking approach used by fuzzy numbers to estimate the interest rate in order to represent real-world situations. Moreover, an algorithm is established to determine the optimal order quantity, the length of the lead time, and the number of lots that are delivered from the vendor to the buyer. Finally, a numerical example is provided to illustrate the solution procedure.

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