Order batching is a general method of grouping a set of orders into several sub sets, i.e., batches. As many warehouses outsource order delivery to a Third Party Logistics (3PL) provider in B2C e-commerce, small lot-size orders arriving dynamically within a certain time period should be grouped into batches and packed up before a fixed departure time. Research on on-line order batching problems, however, seldom takes delivery constraints into consideration. This paper studies the integrated on-line order batching and distribution scheduling problem in which the maximal number of orders has to be completed before the vehicles’ departure time in the shortest service time. Several novel rule-based solutions are proposed, including the formation of batches, which are assigned to appropriate pickers without any information on the arrival times of future orders. Moreover, the solutions define which orders are urgent and should be picked up directly, and which ones can be satisfied later. The solution algorithms are evaluated through a series of experiments. It is demonstrated that these algorithms can lead to a substantial increase of the number of delivered orders, which reveals the importance of integrating order batching with delivery.