Research Article Open Access

Lot-Sizing Decisions under Trade Credit Depending on the Ordering Quantity in Fuzzy Annual Demand

Chui-Yu Chiu, Zhi-Ping Lin and Yi Lin

Abstract

Problem statement: In reality, there are of various products such as liquids, volatile, medicines and materials, in which the rate of deterioration is very large. However, little attention has been mentioned what the effects of deterioration occur in most inventory systems. Also, the loss of the deterioration should not be neglected as an important issue. Approach: In this study, we proposed the problem of determining the Economic Order Quantity (EOQ) for exponentially deteriorating items under the conditions of permissible delay in payments. Recent researches revealed that the payment for the product must be made forthwith when the order quantity is less than the allowable delay in payments. The fixed trade credit period was permitted, or else. Therefore, we utilized the fuzzy theory to implement more considerable answers via numerical examples which were provided to illustrate the results clearly at the end of study. Results: This study discussed the optimal replenishment cycle time for an exponentially deteriorating product under conditions of permissible delay in payments to take the order quantity into account. Conclusion/Recommendations: This study presented another fuzzy environment inventory model which accounts for the permissible delay in payments offered by supplier to the retailer. From the results, it can be concluded that another point of view to decision makers in uncertainty.

American Journal of Applied Sciences
Volume 6 No. 12, 2009, 2060-2065

DOI: https://doi.org/10.3844/ajassp.2009.2060.2065

Submitted On: 12 August 2006 Published On: 31 December 2009

How to Cite: Chiu, C., Lin, Z. & Lin, Y. (2009). Lot-Sizing Decisions under Trade Credit Depending on the Ordering Quantity in Fuzzy Annual Demand. American Journal of Applied Sciences, 6(12), 2060-2065. https://doi.org/10.3844/ajassp.2009.2060.2065

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Keywords

  • Permissible delay in payments
  • fuzzy inventory model
  • deterioration
  • order quantity