Summary: Order picking is conventional warehouse environments involves determining a sequence in which to visit the unique locations where each part in the order is stored, and thus is often modeled as a traveling salesman problem. With computer tracking of inventories, parts may now be stored in multiple locations, simplifying replenishment of inventory and eliminating the need to reserve space for each item. In this environment, order picking requires choosing a subset of the locations that store an item to collect the required quantity. Thus, both the assignment of inventory to an order and the associated sequence in which the selected locations are visited affect the cost of satisfying an order. We formulate a model for simultaneously determining the assignment and sequencing decisions, and compare it to previous models for order picking. The complexity of the order picking problem is discussed, and an upper bound on the number of feasible assignments is established. Several extensions of TSP heuristics to the new problem setting and a tabu search algorithm are presented and experimentally tested.