Modeling Applications in the Airline Industry explains the different functions and tactics performed by airlines during their planning and operation phases. Each function receives a full explanation of the challenges it brings and a solution methodology is presented, supported by numerical illustrative examples wherever possible. The book also highlights the main limitations of current practice and provides a brief description of future work related to each function. The authors have filtered the rich literature of airline management to include only the research that has actually been adopted by the airlines, giving a genuinely accurate representation of real airline management and its continuing development of solution methodologies. The book consists of 20 chapters divided into 4 sections: - Demand Modeling and Forecasting - Scheduling of Resources - Revenue Management - Irregular Operations Management. The book will be a valuable source or a handbook for individuals seeking a career in airline management. Written by experts with significant working experience within the industry, it offers readers insights to the real practice of operations modelling. In particular the book makes accessible the complexities of the key airline functions and explains the interrelation between them.
Arvustused
'While the title suggests this book is only for mathematicians and operational researchers, the clarity of the explanations of the many fascinating problems and issues in this field, make it a rewarding book for anyone with a keen interest in the airline industry. It covers the areas of demand forecasting, scheduling, revenue management and irregular operations.' Aerospace Professional, September 2011
| List of Figures |
|
vii | |
| List of Tables |
|
xi | |
| 1 Introduction to Airline Management |
|
1 | |
| SECTION I DEMAND MODELING AND FORECASTING |
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2 Modeling the Choice of Travel Options |
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|
21 | |
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3 Passenger Demand Modeling and Forecasting |
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|
39 | |
| SECTION II SCHEDULING OF RESOURCES |
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|
|
|
53 | |
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|
|
79 | |
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|
|
89 | |
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|
|
109 | |
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|
|
119 | |
|
9 Flight Planning and Fuel Management |
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|
129 | |
| SECTION III REVENUE MANAGEMENT |
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10 Introduction to Revenue Management |
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141 | |
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11 Demand Forecasting for Revenue Management |
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155 | |
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12 No-show Rate and Overbooking |
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173 | |
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13 Seat Inventory Control for Flight-based Revenue Management Systems |
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181 | |
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14 Seat Inventory Control for Network-based Revenue Management Systems |
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189 | |
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|
205 | |
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|
213 | |
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|
|
221 | |
| SECTION IV IRREGULAR OPERATIONS MANAGEMENT |
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18 Ground Delay Programs and Collaborative Decision Making |
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|
229 | |
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19 Impact of Disruptions on Air Carrier Schedule |
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|
243 | |
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20 Airline Schedule Recovery |
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|
253 | |
| Index |
|
275 | |
Ahmed Abdelghany is an Assistant Professor at the College of Business, Embry-Riddle Aeronautical University. Prior to this he was an Assistant Professor in the Department of Civil and Environmental Engineering, University of Alaska Fairbanks. He worked for four years as a Senior Analyst within the information services division of United Airlines, Chicago. Ahmed holds a Doctorate Degree from the University of Texas at Austin in Civil Engineering (2001) and a Master's Degree in Transportation Engineering from Cairo University, Egypt (1996). He has published in the areas of transportation planning, simulation, operations research, logistics, and airline management. Khaled Abdelghany is an Assistant Professor of Environmental and Civil Engineering at Southern Methodist University in Dallas. He teaches and pursues research in the areas of transportation systems planning and operations management. He also worked as part of the information services division of United Airlines. During his tenure at UA, he was involved in the development of optimization models in the area of airline operation planning and irregular operation management. His research has been published within the Transportation Research Records, Journal of Revenue and Pricing Management, Journal of Air Transport Management, Annals of Operations Research and European Journal of Operational Research.
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