Research Article  Open Access
Neeraj Kumar, S. R. Singh, Rachna Kumari, "An Inventory Model with TimeDependent Demand and Limited Storage Facility under Inflation", Advances in Operations Research, vol. 2012, Article ID 321471, 17 pages, 2012. https://doi.org/10.1155/2012/321471
An Inventory Model with TimeDependent Demand and Limited Storage Facility under Inflation
Abstract
The main objective of this paper is to develop a twowarehouse inventory model with partial backordering and Weibull distribution deterioration. We consider inflation and apply the discounted cash flow in problem analysis. The discounted cash flow (DCF) and optimization framework are presented to derive the optimal replenishment policy that minimizes the total present value cost per unit time. When only rented or own warehouse model is considered, the present value of the total relevant cost is higher than the case when twowarehouse is considered. The results have been validated with the help of a numerical example. Sensitivity analysis with respect to various parameters is also performed. From the sensitivity analysis, we show that the total cost of the system is influenced by the deterioration rate, the inflation rate, and the backordering ratio.
1. Introduction
Deterioration is the change, damage, decay, spoilage, evaporation, obsolescence, pilferage, and loss of utility or loss of marginal value of a commodity that results in decreasing usefulness from the original one. Most products such as medicine, blood, fish, alcohol, gasoline, vegetables, and radioactive chemicals have finite shelf life and start to deteriorate once they are replenished. In addition, for certain types of commodities, deterioration is usually observed during their normal storage period. In most of the inventory models it is unrealistically assumed that during stockout either all demand is backlogged or all is lost. In reality often some customers are willing to wait until replenishment, especially if the wait will be short, while others are more impatient and go elsewhere. The backlogging rate depends on the time to replenishment the longer customers must wait, the greater the fraction of lost sales.
The classical inventory models usually assume that the available warehouse has unlimited capacity. In many practical situations, there exist many factors like temporary price discounts making retailers buy a capacity of goods exceeding their own warehouse (OW). In this case, retailers will either rent other warehouses or rebuild a new warehouse. However, from economical point of views, they usually choose to rent other warehouses. Hence, an additional storage space known as rented warehouse (RW) is often required due to limited capacity of showroom facility. In recent years, various researchers have discussed a twowarehouse inventory system. This kind of system was first proposed by Hartely [1]. In this system, it was assumed that the holding cost in RW is greater than that in OW. By assuming constant demand rate, Sarma [2] developed a deterministic inventory model for a single deteriorating item with shortages and two levels of storage. Pakkala and Achary [3] extended the twowarehouse inventory model for deteriorating items with finite replenishment rate and shortages. Besides, the ideas of timevarying demand for deteriorating items with two storage facilities were considered by Benkherouf [4] and Bhunia and Maiti [5].
Most research on inventory do not consider the time value of money. This is unrealistic, since the resource of an enterprise depends very much on time value of money and this is highly correlated to the return of investment. Therefore, taking into account the time value of money should be critical especially when investment and forecasting are considered. Buzacott [6] was the first author to include the concept of inflation in inventory modeling. He developed a minimum cost model for a singleitem inventory with inflation. Misra [7] simultaneously considered both the inflation and the time value of money for internal as well as external inflation rate and analyzed the influence of interest rate and inflation rate on replenishment strategy. Chandra and Bahner [8] extended the result in Misra’s [7] model to allow for shortages. Sarker and Pan [9] assumed a finite replenishment model and analyzed the effects of inflation and time value of money on order quantity in which shortages were allowed. Hariga [10] extended the study to analyze the effects of inflation and time value of money on an inventory model with timedependent demand rate and shortages. Bose et al. [11] developed an EOQ model for deteriorating items with linear timedependent demand rate and shortages under inflation and time discounting. Van Delft and Vial [12] proposed a simple economic order quantity model for inventory with a short and stochastic lifetime. Their approach was performed in the framework of the total discounted cost criterion. Moon and Lee [13] discussed different types of inventory models with the effects of inflation. For the first time the effect of inflation in twowarehouse system was discussed by Yang [14]. In her study, she considered the constant rate of deterioration in both warehouses with constant demand rate and shortages were completely backlogged. Wee et al. [15] developed twowarehouse inventory model with partial backordering and Weibull distribution deterioration under inflation. In their study, they assumed that the demand and backlogging rate are constant but is not always the case in real life. Yang [16] presented twowarehouse partial backlogging inventory models for deteriorating items under inflation with constant demand rate. Dey et al. [17] developed two storage inventory problems with inflation and time value of money. Ghosh and Chakrabarty [18] suggested an orderlevel inventory model with two levels of storage for deteriorating items and shortages were fully backlogged. Recently, Jaggi and Verma [19] developed a twowarehouse inventory model with linear trend in demand under the inflationary conditions. In their model, shortage was allowed and completely backlogged. Patra [20] presented a twowarehouse inventory model with constant rate of deterioration and time value of money. In his model, shortages are completely backlogged. Singh et al. [21] presented a deterministic twowarehouse inventory model for deteriorating items with partial backlogging. Yang [22] extended Yang [16] model to incorporate threeparameter Weibull deterioration distribution with constant demand.
It has been observed that most researchers on inventory models do not consider timevarying rate of deterioration, inflation, and partial backordering simultaneously. Since this phenomenon is not uncommon in real life, the researchers should also incorporate them in their problem development. In this paper, the researcher has considered a twowarehouse inventory system for deteriorating items. Here, shortages are allowed and partially backlogged. The holding cost at RW is higher as compared to OW. The rate of deterioration in both warehouses is different and follows a twoparameter Weibull distribution. Further, this study takes inflation and applies the discounted cash flow (DCF) approach for problem analysis. In this study, the demand rate is exponentially increasing with time and shortages are partially backlogged with exponential backlogging rate. The discounted cash flow and optimization framework are presented to derive the optimal replenishment policy that minimizes the total present value cost. A numerical example and sensitivity analysis are presented to illustrate all the models. When only rented or own warehouse is considered, the present value of the total relevant cost is higher than the case when twowarehouse model is considered. From the sensitivity analysis, the total cost of the system is influenced by the deterioration rate, the inflation rate, and the backordering ratio.
2. Assumptions and Notations
In developing the mathematical models of the inventory system for this study, the following common assumptions were used.(1)Demand rate is known and is equal to , where and are constants.(2)Shortages are allowed and backlogging rate is , when inventory is in shortage. The backlogging parameter is positive constant and .(3)Deterioration of the item follows a twoparameter Weibull distribution.(4)Deterioration occurs as soon as items are received into inventory.(5)There is no replacement or repair of deteriorating items during the period under consideration.(6)Product transactions are followed by instantaneous cash flow.(7)The holding costs in RW are higher than those in OW.(8)The OW has a fixed capacity of units and the RW has unlimited capacity.(9)Lead time is zero and initial inventory level is zero.(10)The replenishment rate is infinite.
The following notations were used throughout the paper. : Capacity of OW : Scale parameter of the deterioration rate in OW : Shape parameter of the deterioration rate in OW : Scale parameter of the deterioration rate in RW : Shape parameter of the deterioration rate in RW : Inflation rate : Ordering cost per order ($/order) : Holding cost per unit per unit time in OW ($/unit/unit time) : Holding cost per unit per unit time in RW ($/unit/unit time), : Shortage cost per unit time ($/unit/unit time) : Shortage cost for lost sales per unit ($/unit) : Item cost per unit ($/unit) : The order quantity in OW : The order quantity in RW : Maximum inventory level in RW : Time with positive inventory in RW : Time with positive inventory in OW : Time when shortage occurs in OW : Length of the cycle, Inventory level in OW at time : Inventory level in RW at time TUC: The present value of the total relevant cost per unit time.
The rate of deterioration is given as follows. : Time to deterioration, : Probability density function (pdf) of product life : Cumulative distribution function (cdf) of product life : Reliability : Instantaneous rate of deterioration.
From the reliability theory, one has , and . The product life is assumed to follow a twoparameter Weibull distribution. The researcher has assumed as scale parameter, as shape parameter, and . Then one has
The instantaneous rate of deterioration is used in the following model development.
When , deteriorating rate increases with time. When , deteriorating rate decreases with time. And when , deteriorating rate is constant. The twoparameter Weibull distribution reduces to the exponential distribution.
3. Formulation and Solution of the Model
The OW inventory system in Figure 1 can be divided into three phases depicted by to . For each replenishment, a portion of the replenished quantity is used to backorder shortage, while the rest enters the system. units of items are stored in the OW and the rest is dispatched to the RW. The RW is therefore utilized only after OW is full, but stocks in RW are dispatched first. Stock in the RW depletes due to demand and deterioration until it reaches zero. During that time, the inventory in OW decreases due to deterioration only. The stock in OW depletes due to the combined effect of demand and deterioration during time . During the time , both warehouses are empty, and part of the shortage is backordered in the next replenishment.
The OW inventory system can be represented by the following differential equations The firstorder differential equations can be solved using the boundary conditions, ,, and , one has
The RW inventory system can be represented by the following differential equation The firstorder differential equation can be solved using the boundary condition, , one has where
From Figure 1, replenishment is made at , the present worth ordering cost is
Inventory occurs during and time periods. The present worth inventory cost in OW is
Shortages occur during time period. The present worth shortage cost in OW is
Lost sales occur during time period. The present worth lost sale cost in OW is
Replenishment occurs at and . The item cost includes loss due to deterioration as well as the cost of the item sold. The present worth item cost in OW is
From Figure 2, inventory occurs during time periods. The present worth inventory cost in RW is
Replenishment occurs at . The item cost therefore includes loses due to deterioration as well as the cost of the item sold. The present worth cost in RW is
The present value of the total relevant cost during the cycle is
The optimization problem can be formulated as:
In the above expression, TUC is the objective function which we have to minimize, which is the function of , and . To minimize the objective function, the solution methodology is presented in Section 6.
4. When the System Has Only Rented Warehouse (RW)
Figure 3 shows the graphical representation of the RW inventory system having only rented warehouse. The RW inventory level function during and time periods is similar to (3.6) and (3.4). The ordering cost and holding cost of the system are similar to (3.8) and (3.13).
Shortages occur during time period. The present worth shortage cost in RW is Lost sales occur during time period. The present worth lost sales cost in RW is
Replenishment occurs at and . The item cost therefore includes loss due to deterioration as well as the cost of the item sold. The present worth item cost in RW is The order quantity in RW per order is
Noting that , the total present value of the total relevant cost per unit time during the cycle is the sum of ordering cost, holding cost, shortage cost, lost sale cost, and item cost.
In the above expression, is the objective function which we have to minimize, which is the function of and . To minimize the objective function, the solution methodology is presented in Section 6.
5. When the System Has Only Own Warehouse (OW)
Figure 4 shows the graphical representation of the OW inventory system having only own warehouse. The OW inventory level function during and time periods is similar to (3.6) and (3.4). The ordering cost, holding cost, shortage cost, and lost sale cost of the system are similar to (3.8), (3.9), (3.10), and (3.11). The order quantity in OW per order is
Replenishment occurs at and . The item cost therefore includes loss due to deterioration as well as the cost of the item sold. The present worth item cost in OW is
Noting that , the total present value of the total relevant cost per unit time during the cycle is the sum of ordering cost, holding cost, shortage cost, lost sale cost, and item cost
In the above expression, is the objective function which we have to minimize, which is the function of and . To minimize the objective function, the solution methodology is presented in Section 6.
6. Solution Procedure
To derive the optimal solutions, the following classical optimization technique was used.
Step 1. Take the partial derivatives of TUC() with respect to , and and equate the results to zero. The necessary conditions for optimality are
Step 2. The simultaneous equations above can be solved for .
Step 3. With found in Step 2, derive .
7. Numerical Example
Optimal replenishment policy to minimize the total present value cost is derived by using the methodology given in the preceding section. The following parameters are assumed: , ordering cost = 100, holding cost in , holding cost in , shortage cost = 25, lost sale cost = 10, item cost = 10, inflation rate = 0.06, own warehouse capacity = 100, fraction backordered = 0.8, and the deterioration parameters
From the below Table 1 and Figure 5, the main observations drown from the numerical example are as follows:

For Model 1(1)From Table 1, when all the given conditions and constraints are satisfied, the optimal solution is found. In this example, the minimal value of the total present value cost per unit time is $1006.31, while the respective optimal values of , and are 0.53, 4.31, 3.41, and 8.25, respectively. (2)When there is only rented warehouse, the minimal value of the total present value cost per unit time is $2112.41, while the respective optimal period of positive and negative inventory levels are 0.04 and 0.11, respectively. (3) When there is only own warehouse with fixed capacity W units, the minimal value of the total present value cost per unit time is $3378.63, while the respective optimal periods of positive and negative inventory levels are 5.52 and 3.67, respectively. The system has no space to store excess unit and its TUC is higher than our example due to holding cost and shortage cost.
For Model 2(1)From Table 1, when all the given conditions and constraints are satisfied, the optimal solution is found. In this example, the minimal value of the total present value cost per unit time is $1786.38, while the respective optimal values of , and are 0.67, 6.42, 4.11, and 11.20, respectively.(2)When there is only rented warehouse, the minimal value of the total present value cost per unit time is $3755.68, while the respective optimal periods of positive and negative inventory levels are 0.58 and 0.12, respectively.(3)When there is only own warehouse with fixed capacity units, the minimal value of the total present value cost per unit time is $5302.62, while the respective optimal periods of positive and negative inventory levels are 6.27 and 4.23, respectively. The system has no space to store excess unit and its TUC is higher than our example due to holding cost and shortage cost.
For Model 3(1)From Table 1, when all the given conditions and constraints are satisfied, the optimal solution is found. In this example, the minimal value of the total present value cost per unit time is $2506.38, while the respective optimal values of , and are 0.82, 9.49, 5.06, and 15.30, respectively.(2)When there is only rented warehouse, the minimal value of the total present value cost per unit time is $4912.22, while the respective optimal periods of positive and negative inventory levels are 0.09 and 0.13, respectively. (3)When there is only own warehouse with fixed capacity units, the minimal value of the total present value cost per unit time is $6078.92, while the respective optimal periods of positive and negative inventory levels are 8.52 and 5.76, respectively. The system has no space to store excess unit and its TUC is higher than our example due to holding cost and shortage cost.
8. Sensitivity Analysis
In order to study how the parameters affect the optimal solution, the sensitivity analysis is carried out with respect to the various parameters. The results of the sensitivity analysis are presented in Table 2, Figure 6 and Figure 7.

The main observations drawn from the sensitivity analysis are as follows:(1)the value of PCI is the most sensitive to the shape parameter of the deterioration rate and the inflation rate (r). When increases by 20%, the value of PCI increases by over 135%. When r increases by 20%, the value of PCI decreases by over 61%.(2)the values of PCI are quite sensitive to the parameters α and are not so sensitive to the parameters , and .(3)the parameters , and increase proportional to the value of PCI. The PCI is inversely proportional to the parameters .(4) a high parameter value of results in a high value of and . A high parameter value of r results in a small value of , and .
9. Conclusion
In this study, an inventory model is presented to determine the optimal replenishment cycle for twowarehouse inventory problem under inflation, varying rate of deterioration, and partial backordering. The model assumes limited warehouse’s capacity of the distributors. Here, shortages are allowed and partially backlogged. The holding cost at RW is higher as compared to OW. The rate of deterioration in both warehouses is different and follows a twoparameter Weibull distribution. The DCF approach permits a proper recognition of the financial implication of the lost sale in inventory analysis. Some items such as fashionable goods, luxury items, and electronic products are easily identifiable with such kind of a setup, the demand rate is exponentially increasing with time and shortages are allowed and partially backlogged with exponential backlogging rate. The discounted cash flow (DCF) and classical optimization technique are used to derive the optimal replenishment policy. A numerical example and sensitivity analysis are implemented to illustrate the model with the help of MATHEMATICA5.2. When there is only rented or own warehouse in the inventory system, the total present values of the total relevant cost per unit time are higher than the twowarehouse model. From the numerical example, we could finally conclude that model 1 is more profitable in comparison to model 2 and model 3 for twowarehouse inventory system. As the backlogging and deterioration rate increases, the total cost of the system also increases. But as the inflation rate increases, the total cost of the system decreases. From the sensitivity analysis, it is evident that the deterioration rate, the inflation, and the backordering rate affect the total cost of the system. In order to optimize the system, the decision maker must develop the most economical replenishment strategy.
There is ample scope for further extension of the present research study in fuzzy environments, trade credits, and situations of stockdependent demand.
Acknowledgment
The authors wish to thank the referees for their constructive comments and suggestions on the earlier version of the paper.
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Copyright
Copyright © 2012 Neeraj Kumar et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.