Computational Intelligence in Integrated Airline Scheduling (e-bog) af Grosche, Tobias
Grosche, Tobias (forfatter)

Computational Intelligence in Integrated Airline Scheduling e-bog

1240,73 DKK (inkl. moms 1550,91 DKK)
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 smal...
E-bog 1240,73 DKK
Forfattere Grosche, Tobias (forfatter)
Forlag Springer
Udgivet 23 december 2008
Genrer Organizational theory and behaviour
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9783540898870
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.