Abstract
Price optimization fits naturally the framework of bilevel programming, where a leader integrates within its decision process the reaction of rational customers. This paper addresses the situation where the users of a transportation network minimize a weighted sum of travel delay and out-of-pocket cost, each user having its own monetary valuation of travel delay. The resulting infinite-dimensional problem is solved by a hybrid algorithm that alternates between global (combinatorial) and local (descent) phases, and achieves near-optimal solutions under reasonable assumptions.
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