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In this paper, we describe simulation-based stochastic approximation algorithms to find good bid price policies for booking control over an airline network. Our general approach visualizes the total expected profit as a function of the bid prices and searches for a good set of bid prices by using sample path derivatives of the total expected profit function. We demonstrate that the iterates of our stochastic approximation algorithms converge to a stationary point of the total expected profit function with probability one. Our computational experiments indicate that the bid prices computed by our approach perform quite well.