2007International Journal of Operational ResearchRequires access

Replenishment policy for EOQ models with time-dependent quadratic demand and shortages

S.K. Manna, Kripasindhu Chaudhuri, C. Chiang

Open publisher page 24 citations

Abstract

In this paper, we develop two Economic Order Quantity (EOQ) models for quadratic time-varying demand. It is assumed that successive replenishment cycle lengths are in arithmetic progression and γ is the rate of reduction of successive cycle lengths. The model with shortages is studied first. The corresponding results for the model without shortages are derived next. Decision variables are determined numerically for given input parameters. Optimum costs for both the models are also calculated. Computational results show that the model with shortages allowed is economically beneficial. Finally, sensitivity analysis is performed to study the effect of changes in input parameters on the optimal cost.

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What this paper is about

In this paper, we develop two Economic Order Quantity (EOQ) models for quadratic time-varying demand. It is assumed that successive replenishment cycle lengths are in arithmetic progression and γ is the rate of reduction of successive cycle lengths. The model with shortages is studied first. The corresponding results for the model without shortages are derived next. Decision variables are determined numerically for given input parameters. Optimum costs for both the models are also calculated. Computational results show that the model with shortages allowed is economically beneficial. Finally, sensitivity analysis is performed to study the effect of changes in input parameters on the optimal cost.

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Available abstract

In this paper, we develop two Economic Order Quantity (EOQ) models for quadratic time-varying demand. It is assumed that successive replenishment cycle lengths are in arithmetic progression and γ is the rate of reduction of successive cycle lengths. The model with shortages is studied first. The corresponding results for the model without shortages are derived next. Decision variables are determined numerically for given input parameters. Optimum costs for both the models are also calculated. Computational results show that the model with shortages allowed is economically beneficial. Finally, sensitivity analysis is performed to study the effect of changes in input parameters on the optimal cost.

Key concepts: Economic order quantity, Economic shortage, Quadratic equation, Sensitivity (control systems), Reduction (mathematics), Order (exchange), Economics, Mathematical optimization

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