The objective of this collaborative research award is to investigate new methods for designing warehouses that support order picking operations, in which workers visit many locations to build a customer order. The designs will permit picking aisles and cross aisles to take on a number of configurations and angles, which is quite different from current practice, in which picking aisles are parallel and cross aisles are orthogonal to the picking aisles. Warehouse designs will be represented as an encoding of real numbers in an array, which allows for easy manipulation. A significant challenge of the research is to estimate the expected travel distance to retrieve a random order, given a design. A two-stage process will be developed, consisting of a "rough cut" meta-model and a more detailed, simulation-based model. The search space will be explored with particle swarm optimization.
If the research is successful, the methods developed could be used by wholesale and retail distribution centers to reduce labor costs associated with retrieving customer orders. It is estimated that U.S. firms alone spend approximately $13B annually on order picking labor costs. Even a small percentage reduction in this cost could lead to significant economic benefit. Moreover, results of this research will be promoted through an interactive warehouse design website that could be used by students, researchers, and practitioners. The research will also be disseminated by involving students in a tour of existing warehouse facilities, and by distributing teaching modules that can be used in classrooms or distributed over the Web.
