Abstract
The algebraic arithmetic-geometric mean inequality method (the algebraic AGM method) is used to derive the optimal lot size and the optimal backorders level for the EOQ and EPQ models with backorders and defective items introduced by [6]. The method is easy to derive both the optimal lot size and optimal backorders level without derivatives. AMS Subject Classification: 90B05
Highlights
In the context of the deterministic inventory models, the most valuable findings have concerned the economic order/production quantity (EOQ/EPQ) models with/without shortages
In previous several articles, the optimal solution for these models have been derived by differential calculus approach
An optimization approach : the arithmetic-geometric mean (AGM) inequality and the CauchyBunyakovsky-Schwarz (CBS) inequality, which proposed by Cardenas-Barron [2]
Summary
In the context of the deterministic inventory models, the most valuable findings have concerned the economic order/production quantity (EOQ/EPQ) models with/without shortages. An optimization approach : the arithmetic-geometric mean (AGM) inequality and the CauchyBunyakovsky-Schwarz (CBS) inequality, which proposed by Cardenas-Barron [2] This approach is simpler than the algebraic approach, presented by [5] and [1], for deriving the EOQ and EPQ models with backorders. Huang [6] assumed 100% inspection policy and the known proportion of defective items was removed prior to store or use at the end of the screening process He used the algebraic method of [5] and [1] to derive the optimal lot size and the optimal backorders level for the EOQ and EPQ models with backorders and defective items. We apply the algebraic method and the AGM inequality (the algebraic AGM method) to derive the optimal lot size and the optimal backorders level for the EOQ and EPQ models with backorders and defective items
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