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In this work, we present results on airplane boarding strategies. We formulate the airplane boarding problem as an integer programming problem and compare the performance of existing boarding strategies using simulation. The main conclusion is that back-to-front boarding, which is still commonly used by many airlines today, is one of the slowest ways to board an airplane. Also, the amount of carry-on luggage significantly affects the total boarding time no matter what boarding strategy is used.
Keywords: Passenger boarding, group boarding, zone boarding, efficient boarding patterns, airplane boarding by integer programming, airplane boarding by simulation.
Automated planning is concerned with developing automated methods for generating and reasoning about sequences of actions to perform certain tasks or achieve certain goals. Since reasoning about a course of actions to achieve desired outcomes is an important hallmark of intelligent behavior, automated planning has been one of the longstanding sub-areas of artificial intelligence (AI). Most progress in automated planning, to-date, has been driven by the interest in efficiently generating plans under a variety of system dynamics. This work aims to bring the issues of plan quality and optimality to the foreground, by bringing operations research (OR) techniques to bear on automated planning problems.
Keywords: Artificial intelligence planning, automated planning, optimal planning, planning by integer programming.