Paper id 21201462

E-ISSN: 2321–9637
Volume 2, Issue 1, January 2014
International Journal of Research in Advent Technology
Available Online at: http://www.ijrat.org
86
AN INVENTORY MODEL FOR
DETERIORATING ITEMS WITH TIME
DEPENDENT DEMAND UNDER PARTIAL
BACKLOGGING
Milu Acharya1
, Smrutirekha Debata2
1
Department of Mathematics, SOA University, Bhubaneswar, Odisha
Email:milu_acharya@yahoo.com
2
Research Scholar, Department of Mathematics, Utkal University, Bhubaneswar, Odisha
Email:smruti_math@yahoo.com
ABSTRACT- In this work, we study the inventory replenishment policy over a fixed planning period for a
deteriorating item having a deterministic demand pattern with a linear trend and shortages. The model is solved
analytically by minimizing the total inventory cost. The model can be applied to optimize the total inventory
cost for the business enterprises where both the holding cost and deterioration rate are constant.
Keywords: Inventory model, Deteriorating items, Time-dependent demand
1. INTRODUCTION
In recent years, many researchers have studied inventory models for perishable items such as electronic
components, food items, drugs and fashion goods. In many real life situations such as failure of batteries as they
age, spoilage of foodstuffs, and evaporation of volatile liquids, the effect of determination on the replenishment
policies should not be neglected. In fact the stock level of the inventoried item is continuously depleting due to
the combined effects of its demand and deterioration. In the last few years, considerable attention has been given
to inventory lot-sizing models with deterioration.
Inventory problems involving time variable demand patterns have received the attention of several researchers
in recent years. Silver and Meal [1] constructed an approximate solution procedure for the general case of a
deterministic, time varying demand pattern. The classical no-shortage inventory problem for a linear trend in
demand over a finite time horizon was analytically solved by Donaldson [2]. However, Donaldson’s solution
procedure was computationally complicated. Silver [3] derived a heuristic for the special case of positive, linear
trend in demand and applied it to the problem Donaldson. Ritchie [4] obtained an exact solution, having the
simplicity of the EOQ formula, for Donaldson’s problem for linear, increasing demand. Mitra et al. [5]
presented a simple procedure for adjusting the economic order quantity model for the cases of increasing or
decreasing linear trend in demand. In all these models, the possibilities of shortages and deterioration in
inventory were left out of consideration.
Harris [6] developed the first inventory model, Economic Order Quantity, which was generalized by Wilson [7]
who introduced a formula to obtain EOQ. Witin [8] considered the deterioration of the fashion goods at the end
of prescribed shortage period. Dave and Patel [9] studied a deteriorating inventory with linear increasing
demand when shortages are not allowed. Ghare and Schrader [10] addressed the inventory lot-sizing problem
with constant demand and deterioration rate. With the help of some mathematical approximations, they
developed a simple Economic Order Quantity, EOQ, model. Then, Covert and Philip [11] and Tadikamalla [12]
extended Ghare and Schrader’s work by considering variable rate of deterioration. Shah [13] provided a further
generalization of all these models by allowing shortages and using a general distribution for the deterioration

E-ISSN: 2321–9637
87
rate. Other authors [14-18] readjusting Ghare and Schrader’s model by relaxing the assumption of infinite
replenishment rate.
All these inventory models were formulated in a static environment where the demand is assumed to be constant
and steady over a finite planning horizon. However, in a realistic product life cycle, demand is increasing with
time during the growth phase. Naddor [19] assumed a demand function that increasing in linear proportion with
time during the growth phase and analyzed the cost performances of three inventory policies. Mandal [20]
studied a EOQ model for Weibull distributed deteriorating items under ramp-ype demand and shortages. Mishra
and Singh [21, 22] constructed an inventory model for ramp-type demand, time dependent deteriorating items
with salvage value and shortages and deteriorating inventory model for time dependent demand and holding cost
and with partial back logging. Hung [23] investigated an inventory model with generalized type demand,
deterioration and back order rates. In this paper, we made the work of Mishra et al. [24] more realistic by
considering time dependent demand and developed an inventory model for deteriorating items where
deterioration rate and holding cost are constants. Shortages are allowed and partially backlogged.
2. NOTATION AND ASSUMPTION
The fundamental assumption and notation used in this paper are given as below:
a. The demand rate is time dependent and linear, i. e. D(t)=a+bt; a, b>0 and are constant.
b. The replenishment arte is infinite, thus replenishment is instantaneous.
c. I(t) is the level of inventory at time t, Tt ≤≤0 .
d. T is the length of the cycle.
e. θ is the constant deteriorating rate, 10 << θ .
f. 1t is the time when the inventory level reaches zero.
g.
*
1t is the optimal point.
h. Q is the ordering quantity per cycle.
i. 0A is the fixed ordering cost per order.
j. 1C is the cost of each deteriorated item.
k. 2C is the inventory holding cost per unit per unit of time.
l. 3C is the shortage cost per unit per unit of time.
m. S is the maximum inventory level for the ordering cycle, such that S=I(0).
n. )( 11 tC is the average total cost per unit time under the condition Tt ≤1 .
3. MATHEMATICAL FORMULATION
Here we consider the deteriorating inventory model with linearly time dependent demand rate. Replenishment
occurs at time t=0 when the inventory level attains its maximum. From t=0 to t1, the inventory level reduces due

E-ISSN: 2321–9637
88
to demand and deterioration. At t1, the inventory level achieves zero, then shortage is allowed to occur during
the time interval (t1, T) is completely backlogged. The total number of backlogged items is replaced by the next
replenishment. According to the notations and assumptions mentioned above, the behavior of inventory system
at any time can be described by the following differential equations:
)()(
)(
tItD
dt
tdI
θ−−= , 10 tt ≤≤ (1)
)(
)(
tD
dt
tdI
−= , Ttt ≤≤1 (2)
With boundary conditions I(0)=S, I(t1)=0
The solutions of equations (1) and (2) with boundary conditions are as follows.
2
)(
2
1 1
)(
θθθθ
θ bbta
e
bbta
tI tt
+
+
−





−
+
= −
, 10 tt ≤≤ (3)
)(
2
)()( 22
11 Tt
b
TtatI −+−= , Ttt ≤≤1 (4)
The beginning inventory level can be computed as
11
12
)1()0( tt
et
b
e
ba
IS θθ
θθθ
+−





−== (5)
The total number of items which perish in the interval [0, t1], say DT, is
∫∫ +−=−=
11
00
)()(
tt
T dtbtaSdttDSD
2
1112
2
1
)1( 11
btatet
b
e
ba tt
−−+−





−= θθ
θθθ
(6)
The total number of inventory carried during the interval [0, t1], say HT, is
∫=
1
0
)(
t
T dttIH
dt
bbta
e
bbta
t
tt
∫ 





+
+
−





−
+
= −
1
1
0
2
)(
2
1
θθθθ
θ
2
11232
1
2
)1( 1
t
b
t
ba
e
bbta t
θθ
θ
θθ
θ
−
−
−−





−
+
= (7)

E-ISSN: 2321–9637
89
The total shortage quantity during the interval [t1, T], say BT, is
∫−=
T
t
T dttIB
1
)(
∫ 





−+−−=
T
t
dttt
b
tta
1
)(
2
)( 22
11
)32(
6
)2
2
3
(
2
2
1
3
1
3
1
2
1
2
TttT
b
TttT
a
−++−+= (8)
Then, the average total cost per unit time under the condition Tt ≤1 can be given by
][
1
)( 321011 TTT BCHCDCA
T
tC +++= (9)
The first order derivative of C1(t1) with respect to t1 is as follows:
( ) )()(1
1)(
113
2
1
1
11 1
btaTtCe
C
C
Tdt
tdC t
+





−+−





+= θ
θ
(10)
The necessary condition for C1(t1) in (9) to be minimized is
0
)(
1
11
=
dt
tdC
, that is
( ) 0)()(1 113
2
1
1
=+





−+−





+ btaTtCe
C
C tθ
θ
(11)
Let ( ) 





−+−





+= )(1)( 13
2
11
1
TtCe
C
Ctg tθ
θ
Since g(0)=-C3T<0, 0)1)(()( 2
1 >−+= T
e
C
CTg θ
θ
for 1>T
eθ
and 0)()( 3211
1
>++=′ CeCCtg tθ
θ , it implies that g(t1) is a strictly monotonic increasing
function and equation (11) has unique solution at t1
*
, for t*
1ϵ(0, T)
Therefore, we have
Property-1
The deteriorating inventory model under the condition Tt ≤< 10 , C1(t1) obtains its minimum

E-ISSN: 2321–9637
90
at t1=t*
1, where g(t*
1)=0 if t*
1<T.
4. CONCLUSION
In this paper, we study the inventory model for deteriorating items with linear time dependent demand rate. We
proposed an inventory replenishment policy for this type of inventory model. Of course, the paper provides an
interesting topic for the further study of such kind of important inventory models, the following two problems
can be considered in our future research. (1) There is no set up cost in this inventory model. What will happen,
if we add set up cost in to this inventory model? (2) How about the inventory model starting with shortages?
References
[1] Silver, E. A.; Meal, H. C. (1973): A heuristic for selecting lot size quantities for the case of a deterministic time varying
demand rate and discrete opportunities for replenishment. Prod. Invent. Mgmt, 14, 64-74.
[2] Donaldson, W. A. (1977): Inventory replenishment policy for a linear trend in demand-an analytical solution. Opl. Res.
Q., 28, 663-670.
[3] Silver, E. A. (1979): A simple inventory decision rule for a linear trend in demand. J. Opl. Res. Soc., 30, 71-75.
[4] Ritchie, E. (1984): The EOQ for linear increasing demand: a simple optimal solution. J. Opl. Res. Soc., 35, 949-952.
[5] Mitra, A.; Cox, J. F.; Jesse, R. R. (1981): A note on deteriorating order quantities with a linear trend in demand. J. Opl.
Res. Soc., 35, 141-144.
[6] Harris, F. W. (1915): Operations and cost. A. W. Shaw Company, Chicago.
[7] Wilson, R. H. (1934): A scientific routine for stock control. Harv. Bus. Rev., 13, 116-128.
[8] Whitin, T. M. (1957): The theory of inventory management, 2nd
edition, Princeton University Press, Princeton.
[9] Dave, U.; Patel, L. K. (1981): (T, Si) Policy inventory model for deteriorating items with time proportional demand. J.
Oper. Res. Soc., 32, 137-142.
[10] Ghare, P. M.; Schrader, G. F. (1963): A model for an exponentially decaying inventory. J. Ind. Engineering, 14, 238-
243.
[11] Covert, R. P.; Philip, G. C. (1973): An EOQ model for items with Weibull distribution deterioration. AIIE Trans, 5,
323-326.
[12] Tadikamalla, P. R. (1978): An EOQ model for items with Gamma distribution. AIIE Trans, 10, 100-103.
[13] Shah, Y. K. (1977): An order level lot size inventory model for deteriorating items. AIIE trans, 9, 108-112.
[14] Misra, R. B. (1975): Optimum production lot size model for a system with deteriorating inventory. Int. J. Prod. Res. 13,
495-505.
[15] Mak, K. L. (1982): A production lot size inventory model for deteriorating items. Computers Ind. Engng., 6, 309-317.
[16] Elsayed, E. A.; Teresi, C. (1983): Analysis of inventory system with deteriorating items. Int. j. Prod. Res., 21, 449-460.
[17] Rafaet, F. F.; Wolfe, P. M.; Kldin, H. K. (1991): An inventory model for deteriorating items Computers Ind. Engng, 20,
89-94.
[18] Heng, K. J.; Labban, J.; Linn, R. J. (1991): An order level lot size inventory model for deteriorating items with finite
replenishment rates. Computers Ind. Engng, 20, 187-197.
[19] Naddor, E. (1966): Inventory systems. Wiley, New York.
[20] Mandal, B. (2010): An EOQ model for Weibull distributed deteriorating items under ramp type demand and shortages.
Opsearch, 47, 158-165.
[21] Mishra, V. K.; Singh, L. S. (2011a): Inventory model for ramp type demand, time dependent deteriorating items with
salvage value and shortages. Int. J. Appl. Math. Stat., 23, 84-91.
[22] Mishra, V. K.; Singh, L. S. (2011b): Deteriorating inventory model for time dependent demand and holding cost with
partial backlogging. Int. J. Manage. Sci. Eng. Manage, 6, 267-271.
[23] Hung, K. C. (2011): An Inventory model with generalized type demand, deterioration and backorder rates. Eur. J. Oper.
Res., 208, 239-242.
[24] Mishra, V. K.; Singh, L.; Kumar, R. (2013): An inventory model for deteriorating items with time dependent demand
and time varying holding cost under partial backlogging. J. Indst. Eng. Int., 9, 4-8.

Paper id 21201462

More Related Content

Viewers also liked (20)

Similar to Paper id 21201462 (20)

More from IJRAT (20)

Paper id 21201462