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Broadcast is a scalable way of disseminating data because broadcasting an item satisfies all outstanding client requests for it. However, because the transmission medium is shared, individual requests may have high response times. In this paper, we show how to minimize the average response time given multiple broadcast channels by optimally partitioning data among them. We also offer an approximation algorithm that is less complex than the optimal and show that its performance is near-optimal for a wide range of parameters. Finally, we briefly discuss the extensibility of our work with two simple, yet seldom researched extensions, namely, handling varying sized items and generating single channel schedules.