Service location grouping and pricing in transportation: Application in air cargo

It is a common practice for transportation firms to group together a set of locations that they serve and price their services based on the group that the origin and destination of a service belong to rather than point-to-point. Proper grouping of service locations and correct pricing under this policy is essential to the financial success of firms. In this research, we develop a novel model for transportation firms to simultaneously group service locations and determine group-to-group pricing by considering the price elasticity of customers' demand. We formulate the problem as a mixed-integer nonlinear programming and propose two exact solution algorithms based on decomposition principles. The performances of our algorithms are evaluated using computational experiments and results show that proposed methods are effective.