Reference no: EM133214748 , Length: word count:2300
Flight Path Optimization (Scenario)
A proposed cargo network has been illustrated in Figure 1. The Flight times between two nodes are summarized in Table 1.
Table 2: The planned flight information
Flight
No.
|
Origin
|
Destination
|
Distance
(Miles)
|
Demand
|
Standard
Deviation
|
Departure
|
Arrive
|
301
|
HKG
|
KHH
|
412
|
275
|
29
|
08:00
|
09:30
|
302
|
KHH
|
HKG
|
412
|
270
|
31
|
13:00
|
14:30
|
303
|
HKG
|
WUH
|
584
|
128
|
30
|
08:30
|
10:00
|
304
|
WUH
|
HKG
|
584
|
155
|
26
|
16:30
|
18:00
|
Table 3: the seat capacity and estimated fleet operating data for A330 and A320
|
Seat
|
CASM($)
|
RASM($)
|
A330
|
293
|
0.046
|
0.095
|
A320
|
172
|
0.042
|
0.095
|
Task 1
You need to apply the Linear Integer Programming technique in Microsoft Excel's Solver (or LpSolve or R) to work out the shortest route and minimum flight time from node 1 to 9 of the cargo network according to the total flight times given in Table 1.
Task 2
You are required to present all analysis processes including
State clearly the shortest route and minimum flight time you obtained in your network
Evaluate the formula or function used in your program
Describe how the tool is set up by applying Linear Integer Programming technique to perform the calculation in the program; as well as to illustrate the whole calculating process in your Excel
/ R / LPSovle
Task 3
You need to provide a screen recording (no longer than one minute) on how you run your program (Excel Solver/LpSolve/R) to get the solutions.
Table1: Flight times of each city pair of the network of Figure 1
Node(From)
|
Node (To)
|
Network
|
1
|
2
|
35
|
1
|
3
|
65
|
1
|
4
|
36
|
2
|
3
|
28
|
2
|
5
|
32
|
2
|
7
|
55
|
3
|
2
|
36
|
3
|
4
|
15
|
3
|
5
|
18
|
3
|
9
|
75
|
4
|
5
|
35
|
4
|
6
|
28
|
5
|
4
|
26
|
5
|
6
|
13
|
5
|
7
|
12
|
5
|
8
|
28
|
5
|
9
|
25
|
6
|
5
|
11
|
6
|
8
|
16
|
7
|
2
|
32
|
7
|
8
|
20
|
7
|
9
|
13
|
8
|
5
|
15
|
8
|
7
|
18
|
8
|
9
|
23
|
Q2 Fleet Assignment (Scenario)
ABC Airways has decided to start Non-stop flights from Hong Kong International Airport (HKG) to the following cities: Kaohsiung (KHH) and Wuhan (WUH).
Marketing and planning department have provided the passenger demand forecasting and flight details of those two routes, which are shown in Table 2. The Airline plans to adopt two aircrafts: one A330 and one A320. The seat capacity and estimated fleet operating data have been provided in Table 3.
You are required to write a report to apply the fleet assignment approach and tools to work out the following TASKS:
Task 1
Conduct the critical analysis of the fleet operating costs and passenger-spill costs. To obtain the passenger spill number, you need to replicate randomly at least 20,000 times. Assume Sun Airline has a 15% recapture rate. All calculations and detailed explanations should be included in this analysis.
Task 2
Apply the Time-Space network approach to generate the Time-Space network for each airport with aircraft balance constraints. Describe in detail how graphs and aircraft balance constraints support to solve the fleet assignment problem.
Task 3
Address and explain the fleet assignment constraints of your fleet assignment model and calculation.
Task 4
Apply the FAM (Fleet Assignment Model) and the Linear Integer Programming technique to complete a comprehensive fleet assignment plan for the flights in Table 2 and generate a final fleet assignment Time-Space network diagram to allocate your results in FAM. Explain and verify the model and results.
Report Writing
You will need to adopt the report structure provided below:
Introduction
The main body of the Report
Conclusion
References
Use examples and cases from text books, journals, papers and reports to support your arguments and reference properly, using CU Harvard Reference Style.
Q3 Departure Simulation (Scenario)
Hong Kong International Airport (HKIA) is one of the world's busiest passenger airport and cargo gateway. During the fiscal year ended 31 March 2019, the airport handled 428,870 flight movements and served 75.1 million passengers1.
As for the impact of COVID-19 and the enhancement of touchless airport experience, the airport management is reviewing the performance of check-in services in some areas for facilities reallocation and upgrade. You are required to simulate the departure process base on the information provided.
Flightnumber
|
ExpectedDepartureTime
|
Destination
|
HX628
|
14:20
|
Seoul/ICN
|
SQ883
|
14:25
|
Singapore
|
CX418
|
14:25
|
Seoul/ICN
|
CX6112
|
14:35
|
Beijing/PEK
|
Table 1 listed out some information of the observed flights.
Assume the following Arrival Procedures would be performed in HKIA2:
Passengers arrive at Check-in area. (Level 7, Terminal 1, HKIA)
Passengers have check-in baggage:
Used online check-in will directly go to Self-Bag Drop Counter
Did not use online check-in
will go to Check-in Service Counter (with airline staff or handling agent) and drop baggage at the same counter
will go to Kiosk Self Check-in machine and will further go to assigned Self-Bag Drop Counter for Baggage Drop-off if they check in successfully by using Kiosk.
Passenger who have check-in problems with the Kiosk machine will then go to Check-in Service Counter
Passengers have no check-in baggage:
used online check-in will directly go to security check
Did not use online check-in
will go to Check-in Service Counter
Kiosk Self Check-in machine
All passenger will go to security check after finished the check-in and bag drop procedure.
Table 2 listed out the average expected number of passengers and the percentage of passengers who used online check-in before they arrived at airport.
Flightnumber
|
Expectednumberofpassengers
|
Usedonlinecheck-in
|
HX628
|
60-70
|
80%
|
SQ883
|
80-90
|
85%
|
CX418
|
60-70
|
95%
|
CX6112
|
100-120
|
85%
|
Table 3 listed out the percentage of passengers who used online check-in and carrying check-in baggage to departure hall and, and percentage of passengers who did not use online check-in and carrying check-in baggage to departure hall.
|
withcheck-inbaggage
|
UsedOnlineCheck-in
|
70%
|
DidnotuseOnlineCheck-in
|
50%
|
Table 3: Percentage of passengers who are carrying check-in baggage with or without using online check-in
Table 4 listed out the percentage of passengers who did not use online check-in with check-in baggage will go to check-in counter or Kiosk and the percentage of passengers who did not use online check-in without check-in baggage with go to check-in counter or Kiosk.
|
Check-inCounter
|
Self-Check-inKiosk
|
DidnotuseOnlineCheck-inandwithCheck-inBaggage
|
80%
|
20%
|
DidnotuseOnlineCheck-inandwithoutCheck-inBaggage
|
20%
|
80%
|
Table 4: Percentage of passengers who will go to check-in counter or Kiosk with or without check-in baggage
For Self Check-in Kiosk machine:
3 single queue Self Check-in machine are available for the above flights and average processing time is in triangular distribution with (2, 4, 7) minutes
20% of passengers have check-in problem and need to go to Check-in Service Counter
10% of passengers have check-in baggage and they need to go to Self-bag drop counter after successful check-in in Kiosk.
70% of passengers with no check-in baggage and can directly go to Security Check after successful check-in in Kiosk.
For Check-in Counter:
a) 3 single queue Check-in counter are available for the above flights and average processing time is in triangular distribution with (3, 5, 7) minutes
For Self Bag Drop Machine:
a) 3 single queue Self Bag Drop Machine are available for the above flights and average processing time is 5 minutes
You are required to write a report on the above study which includes:
Task 1
An introduction to the simulation, which includes aims & objectives, assumptions (other than the given requirements for the modelling), measurements (e.g. time unit, simulation runs, KPIs concerned or any calculations for the simulation setting) and any other relevant information which is appropriate with brief descriptions.
Task 2
A flowchart to model the simulation with proper labels and notation specification.
Task 3
A SIMUL8 model for the above system ("As-Is" situation). Five simulation runs are required.
An appraisal for the simulation results. (e.g. describe the results with KPIs)
Task 4 (5%)
An animation in the "As-Is" model you developed in Task4 for any one run.
Task 5 (10%)
Recommendations for further improvement (bullet points); each significant improvement will be counted up to 2% with interpretations.
Report Writing (10%)
You will need to adopt the report structure provided below:
Introduction
The main body of the Report
Conclusion
References
Use examples and cases from text books, journals, papers and reports to support your arguments and reference properly, using CU Harvard Reference Style.