Computational Intelligence in Integrated Airline Scheduling

By: Tobias Grosche

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Hardcover | 26 February 2009

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272 Pages

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23.5 x 15.5 x 1.91

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An airline schedule represents the central planning element of each airline. In general, the objective of airline schedule optimization is to find the airline schedule that maximizes operating profit. This planning task is not only the most important but also the most complex task an airline is confronted with. Until now, this task is performed by dividing the overall planning problem into smaller and less complex subproblems that are solved separately in a sequence. However, this procedure is only of minor capability to deal with interdependencies between the subproblems, resulting in less profitable schedules than those being possible with an approach solving the airline schedule optimization problem in one step. In this work, two planning approaches for integrated airline scheduling are presented. One approach follows the traditional sequential approach: existing models from literature for individual subproblems are implemented and enhanced in an overall iterative routine allowing to construct airline schedules from scratch. The other planning appraoch represents a truly simultaneous airline scheduling: using metaheuristics, airline schedules are processed and optimized at once without a separation into different optimization steps for its subproblems.

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Mathematics Applied Mathematics Engineering & Technology Transport Technology & Trades Automotive Technology & Trades Business & Management Organisational Theory & Behaviour Graphical & Digital Media Applications

Computer-Aided Design CAD Technology in General Engineering in General Maths for Engineers Business Strategy

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Published: 28th October 2010

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Introduction	p. 1
Overview	p. 1
Objective	p. 5
Structure	p. 5
Airline Scheduling Process	p. 7
Introduction	p. 7
Airline Scheduling	p. 7
Outline	p. 10
Flight Schedule Generation	p. 12
Problem	p. 12
Solution Models	p. 16
Aircraft Scheduling	p. 18
Problem	p. 18
Solution Models	p. 22
Crew Scheduling	p. 25
Problem	p. 25
Solution Models	p. 29
Integrated Models	p. 34
Overview	p. 34
Models	p. 35
Summary, Conclusion, and Future Challenges	p. 42
Summary	p. 42
Conclusion	p. 44
Future Challenges	p. 45
Foundations of Metaheuristics	p. 47
Introduction	p. 47
Metaheuristic Optimization	p. 48
Design Elements of Metaheuristics	p. 49
Solution Representation and Variation Operators	p. 50
Fitness Function	p. 51
Initialization	p. 52
Search Strategy	p. 52
Selected Metaheuristic Optimization Techniques	p. 53
Local Search: Threshold Accepting	p. 53
Recombination-Based Search: Genetic Algorithms	p. 54
Summary	p. 57
Integrated Airline Scheduling	p. 59
Introduction	p. 59
Motivation	p. 59
Structure	p. 61
Data	p. 61
Schedule Evaluation	p. 66
Overview	p. 66
Market Size Estimation	p. 68
Itinerary Construction	p. 77
Itinerary Market Share Estimation	p. 84
Passenger Allocation	p. 95
Profit Estimation	p. 97
Summary	p. 97
Sequential Approach	p. 99
Overview	p. 99
Solution Steps	p. 100
Solution Process	p. 113
Experiments	p. 118
Summary and Conclusion	p. 126
Simultaneous Approach	p. 129
Overview	p. 129
Conceptual Design	p. 129
Experiments	p. 141
Summary and Conclusion	p. 155
Evaluation	p. 156
Comparison	p. 157
Experimental Verification	p. 161
Summary	p. 166
Summary, Conclusion, Limitations, and Future Work	p. 167
Summary	p. 167
Conclusion	p. 168
Limitations	p. 169
Future Work	p. 170
Summary, Conclusions, and Future Work	p. 173
Summary	p. 173
Conclusion	p. 175
Future Work	p. 175
Aircraft Data	p. 177
Experimental Setups	p. 179
Scenario A	p. 180
Scenario B	p. 180
Scenario C	p. 180
Scenario D	p. 180
Scenario E	p. 181
Experimental Results	p. 183
Calibration	p. 184
Sequential Approach	p. 184
Simultaneous Approach	p. 190
Analysis	p. 199
Sequential Approach	p. 199
Simultaneous Approach	p. 211
Evaluation	p. 228
References	p. 231
Glossary	p. 249
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Computational Intelligence in Integrated Airline Scheduling

At a Glance

Hardcover

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Other Editions and Formats

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