Order picking is one of the most laborious and high-cost processes in the warehouse management and operation. Pickers retrieve goods from their storage locations in order to satisfy orders. The order batching problem(OBP) is a planning problem, which is critical for order picking. Customer orders are grouped into batches in such a way that the total travel distance of all pickers is minimized. First, in order to tackle the assignment of orders to obtain high quality batches, the hybrid metaheuristic algorithm is proposed, which incorporates an infeasible descent procedure into the adaptive large neighborhood search framework. An adaptive punishment mechanism, removal heuristics related to customer orders or batches and additional algorithmic components are also introduced. Second, to address the picker routing and hence reduce batch travel time, the unidirectional heuristic is proposed using a dynamic programming approach to combine routing heuristics. By means of computational experiments, the proposed algorithm is compared to the ALNS/TS and the MS-VNS. It is demonstrated that, in reasonable computing times, the algorithm provides solutions of excellent quality which lead to a reduction of the total travel distance by up to 22.36%.