Abstract
This paper investigates inventory-production systems where items fo llo w constant deterioration. The objective is to develop an optimal policy that min imizes total average cost. The quadratic demand technique is applied to control the problem in order to determine the optimal production policy, holding cost and cost of deterioration. Sensitivity analysis is conducted to study the effect of the cost parameters on the objective function.
Highlights
The purpose of the present paper is to give a new dimension to the inventory literature on time varying demand patterns
The main Limitation in linear time-vary ing demand rate is that it implies a uniform change in the demand per unit t ime
The present authors feel that an exponential rate of change in demand is extraord inarily high and the demand fluctuation of any commodity in the real market cannot be so high .A realistic approach is to think o f accelerated growth in the demand rate in the situations cited above and it can be best represented by a quadratic function of time
Summary
The purpose of the present paper is to give a new dimension to the inventory literature on time varying demand patterns. Me models have been developed with a demand rate that changes exponentially with time. Decrease very rapidly with t ime. So me modellers suggest that this type of rapid change in demand can be represented by an exponential function of time. The approach of Donaldson (8), Murdeshwar (6,)Sahu and Sukla (10) has tried to derive an exact solution for a fin ite horizon inventory model to obtain the optimal nu mber of replenishments, optimal replen ishment times and the optimal times at which the inventory level fa lls to zero, assuming the demand rate to be linearly t ime dependent and shortages. Hamid (3) presented a heuristic model for determining the ordering schedule when inventory items are subject to deterioration and demand changes linearly over time and obtained an optimal replenishment cycle length. Sensitivity analysis is conducted to study the effect of the cost parameters on the objective function
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