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An EOQ Model with Exponentially Increasing Demand under Two Levels of Storage

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  • B. Chandrasekhara Reddy
  • G. Ranganatham

Abstract

In almost every activity, it is difficult to determine what constitutes the ‘best practice’. Businesses around the world spend millions of dollars searching for ‘best practices’, believing that there is a silver bullet solution that will solve their inventory problems but often don’t know whether it is the ‘best practice’ or not. A known fact is that it is difficult to develop a model that reflects the reality as close as possible simultaneously simply for analysis. For this reason, various models are developed under different contexts. The simplest form of the mathematical model for inventory control is known as Wilson’s EOQ model, which is a convenient decision rule for keeping the stock. It is a well-known fact that this formula is based on heavy assumptions, of which the demand rate being treated as constant over time. This assumption, however, is always not true in the real world. When the demand changes from time to time, the inventory problem becomes dynamic. An extensive research work has been carried out by many researchers in the field of inventory considering different patterns of demand like Constant, Linear, Power pattern, and so on. The present article mainly stresses on two specific aspects, namely exponential increasing demand and two levels of storage, that is, Own Warehouse (OW) and Rented Warehouse (RW). A mathematical model is developed for the case of exponentially increasing demand under two levels of storage and the working of the model is demonstrated numerically.

Suggested Citation

  • B. Chandrasekhara Reddy & G. Ranganatham, 2012. "An EOQ Model with Exponentially Increasing Demand under Two Levels of Storage," Vision, , vol. 16(2), pages 121-127, June.
  • Handle: RePEc:sae:vision:v:16:y:2012:i:2:p:121-127
    DOI: 10.1177/097226291201600205
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    References listed on IDEAS

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    1. Harvey M. Wagner & Thomson M. Whitin, 1958. "Dynamic Version of the Economic Lot Size Model," Management Science, INFORMS, vol. 5(1), pages 89-96, October.
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