reading

Cover
Preface
Section 1
1. 1 Brands of Airlines
  1. 1.1 Schedule Availability
  2. 1.2 Size and Domain of Service
  3. 1.3 Business Model
  4. 1.4 Ownership
  5. 1.5 Network Structure
  6. 1.6 Transport Service Type
  7. 1.7 Network Coverage
2. 2 Airline Network Structure
  1. 2.1 Introduction
  2. 2.2 Time Bank
  3. 2.3 Advantages of the Hub‐and‐spoke Network
  4. 2.4 Limitations of the Hub‐and‐spoke Network
3. 3 Airline Schedule Planning Decisions
  1. 3.1 Definitions
  2. 3.2 Relationships Among Scheduling Decisions
4. 4 Measures of Performance
  1. 4.1 Operating Cost
  2. 4.2 Revenue or Income
  3. 4.3 Net Income (Net Profit) and Operating Profit
  4. 4.4 Flights
  5. 4.5 Available Seat Miles
  6. 4.6 Cost per Available Seat Miles (CASM)
  7. 4.7 CASM‐EX or CASM‐EX Fuel
  8. 4.8 Passengers
  9. 4.9 Revenue Passenger Miles (RPM)
  10. 4.10 Total Revenue per Available Seat Mile (TRASM or Simply RASM)
  11. 4.11 Passenger Revenue per Available Seat Mile (PRASM)
  12. 4.12 Passenger Yield
  13. 4.13 Average Load Factor (LF)
  14. 4.14 Block Hours
  15. 4.15 Aircraft Utilization
  16. 4.16 Stage Length
  17. 4.17 On‐time Performance Measures
  18. 4.18 Aircraft Life Cycle
  19. 4.19 Aircraft Number and Diversification
5. 5 Freedoms of Air Service
6. 6 Slot Availability
  1. 6.1 Level 1 Airports
  2. 6.2 Level 2 Airports
  3. 6.3 Level 3 Airports
Section 2
1. 7 Feasibility of a New Route
  1. 7.1 Business Plan
  2. 7.2 Application of Feasibility Study on a New Airline Route
2. 8 Market Share Models
  1. 8.1 What Is a Model?
  2. 8.2 Model and Historical Data
  3. 8.3 Model Development Example
  4. 8.4 Categorical Dependent Variable
  5. 8.5 Introduction to Discrete Choice Models
  6. 8.6 Itinerary Choice Models
  7. 8.7 Applying Itinerary Choice Models: An Example
3. 9 Profitability Forecasting Models
  1. 9.1 Introduction
  2. 9.2 Model Input
  3. 9.3 Itinerary Builder Module
  4. 9.4 How the Model Works?
  5. 9.5 Load Factor, Market Share, and Market Concentration
4. 10 Partnership Agreements
  1. 10.1 Introduction
  2. 10.2 Regional Airlines
  3. 10.3 Code‐share Agreements
  4. 10.4 Airline Alliances
  5. 10.5 Distribution Channels and Point of Sale
  6. 10.6 Loyalty Programs
  7. 10.7 Corporate Travel
Section 3
1. 11 Basic Fleet Assignment Model (FAM)
  1. 11.1 Introduction
  2. 11.2 Graphical Representation: Time‐staggered Diagram
  3. 11.3 Problem Input
  4. 11.4 Problem Definition and Formulation
  5. 11.5 The Constraints of the Basic Fleet Assignment Problem
2. 12 A Walk‐through Example of the Basic Fleet Assignment Model
  1. 12.1 Problem Definition
  2. 12.2 The Objective Function
  3. 12.3 The Constraints
  4. 12.4 Interconnection Nodes
3. 13 Application of the Basic Fleet Assignment Model
  1. 13.1 Introduction
  2. 13.2 Problem Input
  3. 13.3 Setting the Problem in Excel Solver
  4. 13.4 Solution Interpretation
  5. 13.5 Resources Constraints
  6. 13.6 Additional Constraints
Section 4
1. 14 The Schedule Adjustment Problem
  1. 14.1 Introduction
  2. 14.2 Schedule Adjustment Decisions
  3. 14.3 Problem Formulation
2. 15 Examples on the Schedule Adjustment Problem
  1. 15.1 Flight Deletion
  2. 15.2 Flight Addition
  3. 15.3 Flight Departure Time
Section 5
1. 16 Itinerary‐based Fleet Assignment Model (IFAM)
  1. 16.1 Introduction
  2. 16.2 Spill Cost Estimates and Network Effect
  3. 16.3 Demand Recapture
  4. 16.4 The Flight–Itinerary Interaction
  5. 16.5 The Itinerary‐based Fleet Assignment Problem
2. 17 Example on IFAM
  1. 17.1 Problem Definition
  2. 17.2 The Constraints of the IFAM Example
  3. 17.3 The Objective Function
  4. 17.4 Problem Solution
3. 18 Comparing FAM and IFAM
  1. 18.1 Problem Definition
  2. 18.2 Problem Solution
Section 6
1. 19 Integrated Schedule Design with the Itinerary‐based Fleet Assignment Model (ISD‐IFAM)
  1. 19.1 Introduction
  2. 19.2 Example of Demand and Supply Interactions
  3. 19.3 Aspects of Demand–Supply Interactions: Demand Correction Factors
  4. 19.4 The Schedule Design and Adjustment Problem
2. 20 Example on ISD‐IFAM
  1. 20.1 Problem Definition
  2. 20.2 The Constraints of the Problem
  3. 20.3 The Objective Function
  4. 20.4 Problem Solving
  5. 20.5 Solution Interpretation
  6. 20.6 Changing the Operations Cost
Section 7
1. 21 Schedule Robustness
  1. 21.1 Introduction
  2. 21.2 Less‐prone‐to‐disruptions Schedules: The Concept of Adding Slack Times
  3. 21.3 Recoverable Flight Schedules
References
Index
End User License Agreement

List of Tables

Chapter 02
1. Table 2.1 List of city‐pairs served by the time bank.
2. Table 2.2 Information of spoke destinations included in the time bank.
Chapter 04
1. Table 4.1 Example of ASM calculation.
2. Table 4.2 Example of RPM calculation.
3. Table 4.3 Calculations for LF for individual flights.
4. Table 4.4 Information of a hypothetical airline with four flights.
5. Table 4.5 Calculations of ASM for a hypothetical airline with four flights.
6. Table 4.6 Calculations of RPM for a hypothetical airline with four flights.
7. Table 4.7 Calculations of LF for individual flights for a hypothetical airline with four flights.
8. Table 4.8 Aircraft portfolio for major US carriers.
9. Table 4.9 Aircraft portfolio for major European carriers.
Chapter 05
1. Table 5.1 Description of the air service freedoms.
Chapter 07
1. Table 7.1 Demand from each feeder.
2. Table 7.2 The choice set of lunch options for each demand group.
3. Table 7.3 The estimated probabilities (in brackets) for each lunch place option for each of the demand feeders.
4. Table 7.4 The estimated demand of the new restaurant.
5. Table 7.5 The estimated markets sizes for the different demand feeding markets.
6. Table 7.6 Itineraries available for the customers of each demand feeding market.
7. Table 7.7 Estimating the demand for each itinerary that includes the proposed flight ATL‐SEA and total demand for the flight ATL‐SEA.
Chapter 08
1. Table 8.1 The different time zones for the US‐based domestic itinerary choice models.
2. Table 8.2 Definitions of explanatory variables included in the itinerary choice models.
3. Table 8.3 The values of the parameters for the itinerary choice models.
4. Table 8.4 Example applying itinerary choice models for four itineraries.
5. Table 8.5 Example applying itinerary choice models for three itineraries.
Chapter 09
1. Table 9.1 Example for calculating the HHI.
Chapter 12
1. Table 12.1 Notations for the assignment cost.
2. Table 12.2 The symbolic representation of the decision variables of the fleet assignment.
3. Table 12.3 The list of additional decision variables for the fleet assignment example.
Chapter 16
1. Table 16.1 Markets and itineraries served by a hypothetical airline.
Chapter 17
1. Table 17.1 The passenger demand and fares of each of the eight itineraries for the IFAM problem.
2. Table 17.2 The operating cost of each flight for each fleet type for the IFAM problem.
3. Table 17.3 The decision variables of fleet assignment for the IFAM example.
4. Table 17.4 The decision variables for the ground arcs and the overnight arcs for the IFAM example.
Chapter 20
1. Table 20.1 The passenger demand and fares on each of the eight itineraries for the ISD‐IFAM problem.
2. Table 20.2 The operating cost of each flight for each fleet type for the ISD‐IFAM problem.
3. Table 20.3 The decision variables of fleet assignment for the ISD‐IFAM example.
4. Table 20.4 The decision variables for the ground arcs and the overnight arcs for the ISD‐IFAM example.
5. Table 20.5 The new operating cost of each flight for each fleet type for the ISD‐IFAM problem.

List of Illustrations

Chapter 02
1. Figure 2.1 Example of a hub‐and‐spoke airline with a single hub at ATL.
2. Figure 2.2 Example of a point‐to‐point network structure.
3. Figure 2.3 Example of connecting itinerary.
4. Figure 2.4 Example of two connecting itineraries.
5. Figure 2.5 Example of several inbound flights connecting to ORD at ATL.
6. Figure 2.6 Example of several inbound flights connecting to ORD and DTW at ATL.
7. Figure 2.7 Example of a time bank at ATL.
8. Figure 2.8 Example of two successive time banks.
9. Figure 2.9 Different hypothetical examples of time bank configurations at ATL.
10. Figure 2.10 Adding more flights in the time bank.
11. Figure 2.11 Demand mix on flight ATL‐ORD in a hub‐and‐spoke network.
12. Figure 2.12 Demand on flight ATL‐ORD in a point‐to‐point network.
13. Figure 2.13 Competition in a hub‐and‐spoke network.
14. Figure 2.14 Competition in a point‐to‐point network.
15. Figure 2.15 Ground time of resources in a time bank.
Chapter 03
1. Figure 3.1 Fleet assignment among three different fleet types.
2. Figure 3.2 An example of an aircraft rotation.
3. Figure 3.3 The rotation of the aircraft over time and space.
4. Figure 3.4 Interaction among the different airline’s schedule planning decisions.
5. Figure 3.5 Interaction between flight frequency and fleet assignment.
6. Figure 3.6 Interaction between flight departure time decision and city‐pair service.
7. Figure 3.7 Interaction between flight departure time and demand.
8. Figure 3.8 Interaction between flight arrival time and fleet assignment.
9. Figure 3.9 Interaction between fleet assignment and departure time decisions.
10. Figure 3.10 Interaction between flight departure time and aircraft rotation.
11. Figure 3.11 Interaction between flight schedule and fleet assignment balance.
12. Figure 3.12 Interaction between aircraft rotation and fleet assignment.
13. Figure 3.13 The S‐curve showing the relationship between seat capacity and market share.
14. Figure 3.14 Interaction between fleet assignment and flight demand.
15. Figure 3.15 Interaction between flight departure time and service frequency.
16. Figure 3.16 Interaction between departure/arrival times of flights and gates availability.
17. Figure 3.17 Interaction between departure/arrival times of flights and crew schedule.
Chapter 04
1. Figure 4.1 Operating revenue for American Airlines and Delta Air Lines for the period 2000–2016.
2. Figure 4.2 Net income for American Airlines and Delta Air Lines for the period 2000–2016.
3. Figure 4.3 Number of flights scheduled by American Airlines and Delta Air Lines for the period 2002–2016.
4. Figure 4.4 Available seat miles for American Airlines and Delta Air Lines for the period 2002–2016.
5. Figure 4.5 CASM for US‐based airlines for Q2 of 2016.
6. Figure 4.6 CASM components for Q2 2016.
7. Figure 4.7 Number of passengers for American Airlines and Delta Air Lines for the period 2002–2016.
8. Figure 4.8 Revenue passenger miles for American Airlines and Delta Air Lines for the period 2002–2016.
9. Figure 4.9 RASM for several US‐based airlines for Q2 of 2016.
10. Figure 4.10 Revenue passenger miles and available seat miles for American Airlines for the period 2002–2016.
11. Figure 4.11 Average load factor for American Airlines and Delta Air Lines for the period 2002–2016.
12. Figure 4.12 Aircraft seat capacity and maximum range.
Chapter 05
1. Figure 5.1 Graphical representation of the air service freedoms.
Chapter 07
1. Figure 7.1 Location of the proposed property.
2. Figure 7.2 Locations of possible demand feeders.
3. Figure 7.3 The different competing lunch options for demand generated out of the hospital.
4. Figure 7.4 Market share of each option in the choice set for the hospital demand.
5. Figure 7.5 Market share of each option in the choice set for the passing traffic.
6. Figure 7.6 A hypothetical airline with two hubs.
7. Figure 7.7 The proposed route ATL‐SEA.
8. Figure 7.8 The possible feeding markets for the new route ATL‐SEA.
9. Figure 7.9 Routes of Airline 2.
10. Figure 7.10 Routes of Airline 3.
11. Figure 7.11 Routes of Airline 4.
12. Figure 7.12 Assumed market share of each itinerary in the MIA‐SEA city‐pair.
Chapter 08
1. Figure 8.1 Example of historical data for the real‐estate model.
2. Figure 8.2 Data analysis tool in Excel 2013.
3. Figure 8.3 Accessing regression in Data Analysis in Excel 2013.
4. Figure 8.4 Model input.
5. Figure 8.5 Model output.
6. Figure 8.6 Choice set of an individual.
Chapter 09
1. Figure 9.1 Description of the profitability forecasting model.
2. Figure 9.2 Example of schedule data in text format.
Chapter 10
1. Figure 10.1 Example of a network of a mainline airline with agreement with a regional airline.
2. Figure 10.2 Example of two routes operated by two airlines participating in a code‐share agreement.
Chapter 11
1. Figure 11.1 Fleet assignment considering three fleet types.
2. Figure 11.2 The airline schedule planning process.
3. Figure 11.3 A graphical representation of a flight connecting stations A and B.
4. Figure 11.4 Example of a ground arc.
5. Figure 11.5 Example of an overnight arc.
6. Figure 11.6 A time‐staggered diagram for four flights and two fleet types.
7. Figure 11.7 Two time‐staggered diagrams for two different fleet types.
8. Figure 11.8 An example of fleet assignment solution with four flights and two fleet types.
9. Figure 11.9 Determining number of aircraft needed for the fleet assignment solution.
10. Figure 11.10 Example of through flights.
11. Figure 11.11 Example of balancing fleet types at a station.
Chapter 12
1. Figure 12.1 The network structure of a hypothetical airline with a hub at ORD.
2. Figure 12.2 Time‐staggered diagram for fleet type e1.
3. Figure 12.3 Time‐staggered diagram for fleet type e2.
4. Figure 12.4 Counting aircraft remaining overnight at the different stations for fleet type e1.
5. Figure 12.5 Counting aircraft remaining overnight at the different stations for fleet type e2.
6. Figure 12.6 The inbound and outbound flights at LAX operated by fleet e1.
7. Figure 12.7 The inbound and outbound flights at SEA operated by fleet type e1.
8. Figure 12.8 The inbound and outbound flights at BOS.
9. Figure 12.9 Efficient fleet balance at BOS with short ground time for the aircraft.
10. Figure 12.10 Fleet balance at BOS with undesirable long ground time for the aircraft.
11. Figure 12.11 Interconnection nodes at BOS for schedule operated by fleet type e1.
12. Figure 12.12 Interconnection nodes at LAX for schedule operated by fleet type e1.
13. Figure 12.13 Interconnection nodes for the schedule operated by fleet type e1.
14. Figure 12.14 Interconnection nodes for the schedule operated by fleet type e2.
15. Figure 12.15 The interconnection nodes at LAX for fleet type e1 illustrating the ground and overnight links.
16. Figure 12.16 The interconnection nodes at SEA for fleet type e1 illustrating the ground and overnight links.
Chapter 13
1. Figure 13.1 The fleet assignment cost for the 16 flights considering the two fleet types.
2. Figure 13.2 The fleet assignment decision variables for the 16 flights and the two fleet types.
3. Figure 13.3 Initial values of the fleet assignment decision variables.
4. Figure 13.4 The sum of the decision variables for each flight.
5. Figure 13.5 The fleet assignment cost for flights assigned to fleet type e1.
6. Figure 13.6 The fleet assignment cost for flights assigned to fleet type e2.
7. Figure 13.7 Adding the remaining overnight and ground decision variables.
8. Figure 13.8 Calculating the total cost of the fleet assignment problem.
9. Figure 13.9 The value of the total incurred cost in cell O3.
10. Figure 13.10 Tabular format for the balance constraints.
11. Figure 13.11 Defining the LHS of the balance constraint for the first interconnection node at LAX for fleet type e1.
12. Figure 13.12 Defining the RHS of the balance constraint for the first interconnection node at LAX for fleet type e1.
13. Figure 13.13 Defining the LHS of the balance constraint for the second interconnection node at LAX for fleet type e1.
14. Figure 13.14 Defining the RHS of the balance constraint for the second interconnection node at LAX for fleet type e1.
15. Figure 13.15 The calculated values of the left‐hand side and the right‐hand side of the balance constraints for the different interconnection nodes for the two fleet types.
16. Figure 13.16 The Solver function in Microsoft Excel 2013.
17. Figure 13.17 The Solver Parameters window.
18. Figure 13.18 The Add Constraint window in the Excel Solver.
19. Figure 13.19 Entering the coverage constraints.
20. Figure 13.20 The coverage constraints added to the Solver Parameters window.
21. Figure 13.21 Entering the balance constraints for the interconnection nodes at LAX for fleet type e1.
22. Figure 13.22 Entering the balance constraints for the interconnection nodes at SEA for fleet type e1.
23. Figure 13.23 Entering the balance constraints for the interconnection nodes at ORD for fleet type e1.
24. Figure 13.24 The balance constraints added to the Solver Parameters window.
25. Figure 13.25 Entering the binary constraints.
26. Figure 13.26 Entering the integer constraints.
27. Figure 13.27 The binary and integer constraints added to the Solver Parameters window.
28. Figure 13.28 The Solver Results window.
29. Figure 13.29 The fleet assignment solution without resources constraints.
30. Figure 13.30 Graphical representation of the solution of the fleet assignment problem without resources constraints.
31. Figure 13.31 Counting the number of aircraft to remain overnight at the different stations for the fleet assignment problem.
32. Figure 13.32 Adding resources constraints on fleet type e1.
33. Figure 13.33 The fleet assignment solution with a resources constraint.
34. Figure 13.34 Graphical representation of the fleet assignment problem with a resources constraint.
Chapter 15
1. Figure 15.1 Net revenue for the 16 flights when assigned to each fleet type.
2. Figure 15.2 The initial decision variables and the associated net revenues for the schedule adjustment problem for the flight deletion example.
3. Figure 15.3 The calculation of the total incurred net revenue for the schedule adjustment problem for the flight deletion example.
4. Figure 15.4 Counting the number of aircraft to remain overnight at the different stations for the schedule adjustment problem for the flight deletion example.
5. Figure 15.5 The balance constraints for the schedule adjustment problem for the flight deletion example.
6. Figure 15.6 The Solver Parameters window with inputs including the objective function, the decision variables, and the coverage constraints for the schedule adjustment problem for the flight deletion example.
7. Figure 15.7 Adding the balance constraints in the Solver Parameters window for the schedule adjustment problem for the flight deletion example.
8. Figure 15.8 Adding the resources constraints in the Solver Parameters window for the schedule adjustment problem for the flight deletion example.
9. Figure 15.9 Adding the integer and binary constraints in the Solver Parameters window for the schedule adjustment problem for the flight deletion example.
10. Figure 15.10 The schedule adjustment problem for the flight deletion example.
11. Figure 15.11 The solution of the schedule adjustment problem for the flight deletion example.
12. Figure 15.12 The proposed routes for the airline with additional destination at IAD.
13. Figure 15.13 The proposed schedule considering all 20 flights.
14. Figure 15.14 The interconnection nodes for the schedule when operated by fleet type e1 for the flight addition problem.
15. Figure 15.15 The interconnection nodes for the schedule when operated by fleet type e2 for the flight addition problem.
16. Figure 15.16 A snapshot of the Excel sheet representing the decision variables and the net revenue of the flight addition problem.
17. Figure 15.17 A snapshot of the Excel sheet representing the balance constraints of the flight addition problem.
18. Figure 15.18 The Solver Parameters window for the flight addition problem with the objective function, decision variables, and coverage constraints.
19. Figure 15.19 The Solver Parameters window for the flight addition problem with all constraints except resources constraints.
20. Figure 15.20 A snapshot of the optimal solution of the flight addition problem with no resources constraints.
21. Figure 15.21 The Solver Parameters window for the flight addition problem with all constraints including resources constraints.
22. Figure 15.22 The balance and resources constraints for the flight addition problem.
23. Figure 15.23 A snapshot of the optimal solution of the flight addition problem with resources constraints.
24. Figure 15.24 Flights assigned to fleet type e1 for the flight addition problem with resources constraints.
25. Figure 15.25 Flights assigned to fleet type e2 for the flight addition problem with resources constraints.
26. Figure 15.26 The proposed five departure times of flight 16 between LAX and ORD.
27. Figure 15.27 Flight numbers for the proposed copies of flight 16 between LAX and ORD.
28. Figure 15.28 The interconnection nodes for the schedule if operated by fleet type e1 for the flight departure time adjustment problem.
29. Figure 15.29 The interconnection nodes for the schedule if operated by fleet type e2 for the flight departure time adjustment problem.
30. Figure 15.30 A snapshot of Excel sheet that shows the initial values of the decision variables for the flight departure time adjustment problem.
31. Figure 15.31 A snapshot of the Excel sheet that shows the balance constraints for the flight departure time adjustment problem.
32. Figure 15.32 The Solver Parameters window for the flight departure time adjustment problem with the objective function and the coverage constraints.
33. Figure 15.33 The Solver Parameters window for the flight departure time adjustment problem with all constraints.
34. Figure 15.34 A snapshot of the Excel sheet for the flight departure time adjustment problem with the values of the optimal solution.
35. Figure 15.35 Flights assigned to fleet type e1 for the flight departure time adjustment problem.
36. Figure 15.36 Flights assigned to fleet type e2 for the flight departure time adjustment problem.
Chapter 16
1. Figure 16.1 A hypothetical airline with two flights.
2. Figure 16.2 Example used to show the calculations of the unconstrained revenue, the spill cost, and the recaptured revenue.
3. Figure 16.3 A hypothetical airline with several connecting itineraries.
Chapter 17
1. Figure 17.1 An example of a hypothetical airline with six flights for the IFAM problem.
2. Figure 17.2 The interconnection nodes for the IFAM example.
3. Figure 17.3 The decision variables and formulas for cost calculations for the IFAM example.
4. Figure 17.4 The decision variables and initial cost values for the IFAM example.
5. Figure 17.5 The formulas representing the seat capacity of each flight for the IFAM example.
6. Figure 17.6 The initial values of the seat capacity of each flight for the IFAM example.
7. Figure 17.7 The formulas for the balance constraints for the IFAM example.
8. Figure 17.8 The initial values of the balance constraints for the IFAM example.
9. Figure 17.9 The formulas for the unconstrained demand for each flight for the IFAM example.
10. Figure 17.10 The values for the unconstrained demand for each flight for the IFAM example.
11. Figure 17.11 The itinerary–itinerary spill–recapture relationship matrix for the IFAM example.
12. Figure 17.12 The initial values of the spilled demand decision variables for the IFAM example.
13. Figure 17.13 The formulas for the calculations of the total spilled demand for each itinerary for the IFAM example.
14. Figure 17.14 The initial values of the total spilled demand for each itinerary for the IFAM example.
15. Figure 17.15 The transposed form of the itinerary–flight incidence matrix for the IFAM example.
16. Figure 17.16 The formulas for the calculations of the spilled demand at the flight level for the IFAM example.
17. Figure 17.17 The initial values of the spilled demand at the flight level for the IFAM example.
18. Figure 17.18 The calculations of the recaptured demand and recaptured revenue for the IFAM example.
19. Figure 17.19 The initial values of the recaptured demand and recaptured revenue for the IFAM example.
20. Figure 17.20 The calculations of the flight demand characteristics and the objective function of the IFAM example.
21. Figure 17.21 The initial values of the flight demand characteristics and the objective function of the IFAM example.
22. Figure 17.22 The Solver Parameters window for the IFAM example (part 1).
23. Figure 17.23 The Solver Parameters window for the IFAM example (part 2).
24. Figure 17.24 The Solver Results window for the IFAM example.
25. Figure 17.25 The solution of the IFAM example (part 1).
26. Figure 17.26 The solution of the IFAM example (part 2).
27. Figure 17.27 The solution of the IFAM example (part 3).
28. Figure 17.28 The solution of the IFAM example (part 4).
29. Figure 17.29 The solution of the IFAM example (part 5).
30. Figure 17.30 The solution of the IFAM example (part 6).
31. Figure 17.31 The solution of the IFAM example (part 7).
32. Figure 17.32 The solution of the IFAM example (part 8).
33. Figure 17.33 Graphical representation of the solution for the IFAM example.
Chapter 18
1. Figure 18.1 The decision variables and formulas for cost calculation for the comparable FAM example.
2. Figure 18.2 The decision variables and values for cost calculation for the comparable FAM example.
3. Figure 18.3 The formulas representing the seat capacity of each flight for the comparable FAM example.
4. Figure 18.4 The initial values of the seat capacity of each flight for the comparable FAM example.
5. Figure 18.5 The formulas for the balance constraints for the comparable FAM example.
6. Figure 18.6 The initial values of the balance constraints for the comparable FAM example.
7. Figure 18.7 The formulas for the unconstrained demand for each flight for the comparable FAM example.
8. Figure 18.8 The values for the unconstrained demand for each flight for the comparable FAM example.
9. Figure 18.9 The calculation of the flight spilled revenue for the comparable FAM example.
10. Figure 18.10 The flight spilled revenue for the comparable FAM example.
11. Figure 18.11 The Solver Parameters window for the comparable FAM example.
12. Figure 18.12 The Solver Results window for the comparable FAM example.
13. Figure 18.13 The solution of the comparable FAM example (part 1).
14. Figure 18.14 The solution of the comparable FAM example (part 2).
15. Figure 18.15 The solution of the comparable FAM example (part 3).
16. Figure 18.16 The solution of the comparable FAM example (part 4).
Chapter 19
1. Figure 19.1 An example of a hypothetical airline with a hub and a time bank at ATL.
2. Figure 19.2 A hypothetical schedule serving four destinations.
Chapter 20
1. Figure 20.1 An example of a hypothetical airline with six flights for the ISD‐IFAM problem.
2. Figure 20.2 The interconnection nodes for the ISD‐IFAM example.
3. Figure 20.3 The decision variables and formulas for cost calculations for the ISD‐IFAM example.
4. Figure 20.4 The decision variables and initial cost values for the ISD‐IFAM example.
5. Figure 20.5 The formulas representing the seat capacity of each flight for the ISD‐IFAM example.
6. Figure 20.6 The initial values of the seat capacity of each flight for the ISD‐IFAM example.
7. Figure 20.7 The formulas for the balance constraints for the ISD‐IFAM example.
8. Figure 20.8 The initial values of the balance constraints for the ISD‐IFAM example.
9. Figure 20.9 The formulas for the unconstrained demand for each flight for the ISD‐IFAM example.
10. Figure 20.10 The values for the unconstrained demand for each flight for the ISD‐IFAM example.
11. Figure 20.11 The itinerary–itinerary spill–recapture relationship matrix for the ISD‐IFAM example.
12. Figure 20.12 The initial values of the spilled demand decision variables for the ISD‐IFAM example.
13. Figure 20.13 The formulas for the calculations of the total demand spill for each itinerary for the ISD‐IFAM example.
14. Figure 20.14 The initial values of the total demand spill for each itinerary for the ISD‐IFAM example.
15. Figure 20.15 The transposed form of the itinerary–flight incidence matrix for the ISD‐IFAM example.
16. Figure 20.16 The formulas for the calculations of the demand spill at the flight level for the ISD‐IFAM example.
17. Figure 20.17 The initial values of the demand spill at the flight level for the ISD‐IFAM example.
18. Figure 20.18 The formulas for the calculations of the recaptured demand and recaptured revenue for the ISD‐IFAM example.
19. Figure 20.19 The initial values of the recaptured demand and recaptured revenue for the ISD‐IFAM example.
20. Figure 20.20 The calculations of the flight characteristics and the objective function of the ISD‐IFAM example.
21. Figure 20.21 The initial values of the flight characteristics and the objective function of the ISD‐IFAM example.
22. Figure 20.22 The formulas that give revenue change due to the suggested deletion of the optional itineraries for the ISD‐IFAM example (the left‐hand side).
23. Figure 20.23 The revenue change due to the suggested deletion of the optional itineraries for the ISD‐IFAM example (the left‐hand side).
24. Figure 20.24 The formulas that give revenue change due to the suggested deletion of the optional itineraries for the ISD‐IFAM example (the right‐hand side).
25. Figure 20.25 The revenue change due to the suggested deletion of the optional itineraries for the ISD‐IFAM example (the right‐hand side).
26. Figure 20.26 The formulas that show additional calculations for the optional flights for the ISD‐IFAM example (part 1).
27. Figure 20.27 Additional calculations for the optional flights for the ISD‐IFAM example (part 1).
28. Figure 20.28 The formulas that show additional calculations for the optional flights for the ISD‐IFAM example (part 2).
29. Figure 20.29 Additional calculations for the optional flights for the ISD‐IFAM example (part 2).
30. Figure 20.30 The formulas for the calculations of the demand change for each of the alternative itineraries, because of removing the optional itineraries for the ISD‐IFAM example.
31. Figure 20.31 The demand change for each of the alternative itineraries, because of removing the optional itineraries for the ISD‐IFAM example.
32. Figure 20.32 Formulas for calculating main flight characteristics for ISD‐IFAM example.
33. Figure 20.33 Main flight characteristics for ISD‐IFAM example.
34. Figure 20.34 The formulas for the total demand spilled for each itinerary and the total demand of each itinerary for the ISD‐IFAM example.
35. Figure 20.35 The total demand spilled for each itinerary and the total demand of each itinerary for the ISD‐IFAM example.
36. Figure 20.36 The Solver Parameters window for the ISD‐IFAM example (part 1).
37. Figure 20.37 The Solver Parameters window for the ISD‐IFAM example (part 2).
38. Figure 20.38 The Solver Parameters window for the ISD‐IFAM example (part 3).
39. Figure 20.39 The Solver Results window for the ISD‐IFAM example.
40. Figure 20.40 The values of the decision variables at the optimal solution for the ISD‐IFAM example.
41. Figure 20.41 The values of the RHS and LHS for the balance constraints at the optimal solution for the ISD‐IFAM example.
42. Figure 20.42 The values of the spill variables at the optimal solution for the ISD‐IFAM example.
43. Figure 20.43 The value of the total revenue spill and the total revenue recaptured at the optimal solution for the ISD‐IFAM example.
44. Figure 20.44 The value of demand spill and recapture at the flight level at the optimal solution for the ISD‐IFAM example.
45. Figure 20.45 The values of the decision variable Z_q for each optional itinerary at the optimal solution for the ISD‐IFAM example.
46. Figure 20.46 The value of the objective function at optimal solution for the ISD‐IFAM example.
47. Figure 20.47 The values of the problem elements at optimal solution for the ISD‐IFAM example (part 1).
48. Figure 20.48 The values of the problem elements at optimal solution for the ISD‐IFAM example (part 2).
49. Figure 20.49 The values of the problem elements at optimal solution for the ISD‐IFAM example (part 3).
50. Figure 20.50 The values of the problem elements at optimal solution for the ISD‐IFAM example (part 4).
51. Figure 20.51 The decision variables and formulas for cost calculations for the modified ISD‐IFAM example.
52. Figure 20.52 The revenue spill and the revenue recaptured for the modified ISD‐IFAM example.
53. Figure 20.53 The revenue change due to the suggested deletion of the optional itineraries for the modified ISD‐IFAM example.
54. Figure 20.54 The initial value of the objective function for the modified ISD‐IFAM example.
55. Figure 20.55 The Solver Parameters window for the modified ISD‐IFAM example.
56. Figure 20.56 The Solver Results window for the modified ISD‐IFAM example.
57. Figure 20.57 The values of the decision variables at the optimal solution for the modified ISD‐IFAM example.
58. Figure 20.58 The values of the RHS and LHS for the balance constraints at the optimal solution for the modified ISD‐IFAM example.
59. Figure 20.59 The demand spilled between itineraries at the optimal solution for the modified ISD‐IFAM example.
60. Figure 20.60 The spilled and recaptured revenue at the optimal solution for the modified ISD‐IFAM example.
61. Figure 20.61 The demand spill and recapture at the flight level at the optimal solution for the modified ISD‐IFAM example.
62. Figure 20.62 The values of the decision variable Z_q for each optional itinerary at the optimal solution for the modified ISD‐IFAM example.
63. Figure 20.63 The value of the objective function at the optimal solution for the modified ISD‐IFAM example.
64. Figure 20.64 The values of the problem elements at optimal solution for the modified ISD‐IFAM example (part 1).
65. Figure 20.65 The values of the problem elements at optimal solution for the modified ISD‐IFAM example (part 2).
66. Figure 20.66 The values of the problem elements at optimal solution for the modified ISD‐IFAM example (part 3).
67. Figure 20.67 The values of the problem elements at optimal solution for the modified ISD‐IFAM example (part 4).
68. Figure 20.68 The values of the problem elements at optimal solution for the modified ISD‐IFAM example (part 5).
Chapter 21
1. Figure 21.1 The relationship between the actual and the estimated flight block time.
2. Figure 21.2 Example of a slack time of a connecting aircraft.
3. Figure 21.3 Example of the slack time of an inbound flight.
4. Figure 21.4 Example on swapping of airline resources to recover flights.
5. Figure 21.5 The impact of the swapping of the two aircraft on their routes.
6. Figure 21.6 The impact of cancellation on aircraft rotation.
7. Figure 21.7 Multiple swapping opportunities for the aircraft.