• Lindsey McCarty
  • April 13, 1 PM
  • 3866 East Hall
Bender's Decomposition is a powerful method used in solving large  
linear programming problems with a special structure. For example, it  
can be used for two-stage stochastic linear programming problems.   
Using Bender’s Decomposition can make solving these problems much  
quicker, since the complete model is broken down into many smaller  
problems and delayed constraint generation is used.  Another important  
part of Bender’s Decomposition is using the dual of the second-stage  
problem.

In this talk, we will describe the method of Bender’s Decomposition  
and present it as an approach for solving our two-stage stochastic  
model for airline passenger re-accommodation after disruptions.  The  
goal of our model is to improve passenger re-accommodation by acting  
proactively as soon as it is known that a flight will be delayed, use  
known probabilities for the length of delay, and consider all of the  
affected passengers together. Since the length of a delay is often not  
known in advance, we consider preemptive re-routing of airline  
passengers before the length of the delay is known.
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