运营管理计算题类型汇总

How can we get the optimal policy is to allocate 184 seats to Category A and 116 seats to Category B ?
• 02 The total number of customers affect: 188.57cars/hourx(1+5%)x14weeksx5daysx2hours=27720car
• 03 The increased value for customer (or saved value for customer):
Yield management at Transpacific Airlines
How can we get the probability that demand will exceed 180 in Category A is 46 percent.
How can we get the probability that the demand in Category B will exceed the assigned number of seats is equal to 88 percent.
• C*=213
What about no-shows and overbooking?
the probability thatdemand(D) willexceedcapacityis equal to P(D C*) C0
CS C0
Gravity models in retail management(P330)
McDonald has to decide how many seats to provide in a new McDonald in Main Yang, the manager know the demand in Main Yang is normally distributed with an average of 200 seats per day and a standard deviation of 15. One day, the McDonald has to turn away a customer because seats are all occupied, it loses the gross margin on the seat of 40RMB. They also know that if the McDonald has one seat unoccupied on a particular day, the cost is estimated to be 10RMB
What is yield ?
the ratio of revenue
realized over
yrieevldenuererevaelnizueedrealized revenuerpeovteennuteiapl otential
revenue potential
Example (P304)
What’s the optimal number of seats of the McDonald?
•P(D>C*)
=10/(40+10) =0.2
• F(C*)=1-0.2=0.8 P(D C*) P(D
C*C) SCC0CSC00C0
• Z=(C*-200)/15
•查表所得：Z=0.85
27720 x(57.8minutes/60)x12.5euro/hour per car=333795euro • 04 compare:
333795euro>52100euro, so it’s worthwhile expanding the cLeabharlann pacity to 12 lines.
a marginal cost of capacity expansion b cost of waiting per time unit and per customer w the marginal reduction of average waiting time per customer N total number of customers whose average waiting time will be reduced over the time horizon considered
Customer is turned away
In these instances, an approach referred to as marginal analysis can be applied. According to this approach, the optimal capacity level C* is that level for which the probability that demand (D) will exceed capacity is equal to:
Determining the capacity level
• Cost of waiting is known
• Cost of waiting is not known
1 Cost of waiting is known
P288
• 01 Calculate the total cost of the whole year: (15euro/hourx14weeksx5daysx2hours)+50000euro=52100euro
siteA: 0.29*10000*$400=$1 160 000 siteC: 0.38*10000*$400=$1 520 000
Then site C would be most profitable.
Location models(P328)
Site A:
In this case,site A is clearly the best potential site of the four.
2 Cost of waiting is not known
a<b x Δ w x N
b
a
——————
Δ wxN
a
52100euro
—————— = ———————————— = 0.033euro/minutes
Δ w x N 57.8minute sx27720
If b>0.033euro/minute s, expansion can go ahead If b<0.033euro/minute s, expansion should not be considered
The most frequently used model is the Huff model. This model determines the probability (Pij) that a customer, located in a certain area (i), will shop at a particular store or shopping centre ( j).
If we assume that the university has 10,000students,each spending an average of $400 a year on clothes,the annual forecast sales for site A and C will be: