Customer Information Driven After Sales Service ... - RePub
Customer Information Driven After Sales Service ... - RePub
Customer Information Driven After Sales Service ... - RePub
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5.4. Markov Decision Process Formulation<br />
the probability of a false demand signal, the spare part logistics need to decide the<br />
appropriate stock location for spare part return. Note that the spare part return decision<br />
depends on the earlier spare part sourcing decision. The costs of a false demand signal<br />
are f d ij + f r lj ,whereirepresents the source stock location and l represents the candidate<br />
return stock location. Suppose that we decided to source the spare part from stock<br />
location i and a false demand occurred, then we need to maximize the following function<br />
to identify the candidate stock location for spare part return. Similar to the previous<br />
section, �el is unit vector notation with inconsideration l equals one and others as zero.<br />
�<br />
max Vt+1(�x − �ei + �el) − f<br />
l∈L<br />
d ij − f r �<br />
lj<br />
5.4 Markov Decision Process Formulation<br />
Figure 5.1 highlights the interaction between sourcing and return decisions. In this<br />
section, we present two MDP formulations to accommodate this interaction. In the first<br />
formulation, we account for the probability of false demand and consequent spare part<br />
return while deciding for the forward sourcing decision. Similarly, for the return decision,<br />
we account for the preceding sourcing decision from the current time instance t. Inthe<br />
subsequent text, we term this as a bi-directional interaction of the forward sourcing and<br />
return decision. To formalize this interaction, we present the following two stage MDP<br />
formulation. The value of stock �x at time t equals the expected revenue given the optimal<br />
use of the available resources.<br />
V in<br />
t (�x) = � �<br />
λj max (1 − qj){gj − f<br />
i∈M,l∈L<br />
j∈N<br />
d ij − f p<br />
ij<br />
+ V in<br />
t+1(�x − �ei)} + qj{V in<br />
t+1(�x − �ei + �el) − f d ij − f r �<br />
lj}<br />
Observe that we may write,<br />
V in<br />
t (�x) = � �<br />
λj max (1 − qj){gj − f<br />
i∈M<br />
j∈N<br />
d ij − f p in<br />
ij + Vt+1(�x − �ei)}<br />
� in<br />
Vt+1(�x − �ei + �el) − f d ij − f r �<br />
lj<br />
�<br />
+ qj max<br />
l∈L<br />
137<br />
(5.1)