Civil Engineering Reference
In-Depth Information
Tabl e 2
Simulation “single year”
Profit
Price
Hotel
X
Hotel
YA
B
C
10
6
10
6
)
10
4
)
10
4
)
10
4
)
(
×
)
(
×
(
×
(
×
(
×
1
a
1
,
a
2
0.243
0.253
0.234
0.468
0.935
2
a
1
,
b
2
0.282
0.363
0.220
0.441
0.881
3
a
1
,
c
2
0.369
0.127
0.221
0.441
0.882
4
b
1
,
a
2
0.269
0.290
0.224
0.447
0.895
5
b
1
,
b
2
0.315
0.387
0.214
0.428
0.856
6
b
1
,
c
2
0.424
0.160
0.207
0.414
0.827
7
c
1
,
a
2
0.261
0.261
0.213
0.426
0.852
8
c
1
,
b
2
0.274
0.340
0.223
0.447
0.893
9
c
1
,
c
2
0.321
0.147
0.210
0.420
0.840
Tabl e 3
Results of
simulation and evaluation
function
10
6
10
6
Profit
X
:
c
1
(
×
)
Y
:
a
2
(
×
)
Evaluation function
0.270
0.270
Simulation
0.261
0.261
The simulation was pursued 30 times for all the combination of strategies as
shown in Table
2
. Comparing the highest average value in it, different values were
obtained every time because of the random Monte Carlo simulations.
When comparing the results between the Monte Carlo simulation and the
theoretically evaluation function, hotel X with strategy
c
1
and hotel Y with strategy
a
2
, both hotels obtained the highest profits using the evaluation function as shown
in Table
3
.
In the simulation, the total number of customer is determined using random
variables; the evaluation function derives the Bertrand model-Nash equilibrium for
both hotels. And the number of sold rooms in hotels X and Y is derived by the same
result of Bertrand model-Nash equilibrium in evaluation function. In the simulation
the same Bertrand model-Nash equilibrium is used
Z
x
=
80 and the value is
calculated as shown in Table
4
. From this, this simulation has proved to be the
correct. And when these two hotels execute strategy
b
1
&
b
2
, become the optimal
strategy.
Z
y
=
6
Conclusion
The optimum strategy has been developed for hotel yield management in Bertrand
situation. In this study, the number of customers varies randomly by using the
exponential distribution. If we can know the number of guests who stay in the
hotel, we obtain the optimal decision-making strategies by means of using Bertrand
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