Genetic Algorithm for Airline Seat Inventory Control

Airline seat inventory control is a very profitable tool in the airline industry. Mathematical programming models provide booking limits or bid-prices for all itineraries and fare classes based on demand forecasts. The general models include deterministic approximation methods and probabilistic approximation methods, but these models are hard to solve if the number of decision variables and constraints is large. We present a new model for seat inventory control based on genetic algorithm in this paper, and simulate results was compared among the new model and general models. Study shows that Genetic algorithm is profit for seat inventory control, and it is easy to implement.