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To forestall error accumulation attributable to modeling two subtasks independently, we propose to jointly model both subtasks in an end-to-end neural community. We suggest and study a simple mannequin for auctioning such ad slot reservations prematurely. An extensive computational examine demonstrate the efficacy of the proposed approach and gives insights in to the benefits of strategic time slot administration. We propose a 2-stage stochastic programming formulation for the design of a priori supply routes and time slot assignments and a pattern common approximation algorithm for its answer.


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