An Integrated Load-Planning Algorithm for Outbound Logistics at Webb Wheel

Abstract

We present an integrated model for simultaneous optimization of the loading and routing decisions associated with an automotive supplier’s outbound supply chain. The supplier, Webb Wheel (WW), is a manufacturer of brake drums, rotors, hubs, and spoke wheels. WW accepts new orders from customers each day. Given sufficient inventory, it combines these orders into loads, releases them based on various dispatch criteria (e.g., truck-utilization, route-utilization, or penalty-based dispatch policies) and due-date considerations, and ships them in truckloads, less-than-truckloads, and containers. Dynamically changing demand information, inventory rationing, inventory interactions among orders, and lead-time considerations are some of the challenging aspects of the problem. Our optimization model is based on the decomposition of the problem into assignment and routing subproblems. The assignment subproblem determines the transportation mode and carrier choices, while considering total transportation costs. These costs depend on a variety of factors, including destination, number of drop locations on the route, and needs of customers on the route. Given the customer clusters and transportation modes from the assignment subproblem, the routing subproblem determines the sequence of drops and the true cost of the shipment using a modified traveling salesman problem. A scalable database with a graphical user interface supports the optimization model. We test our algorithm using four months of WW data and compare these data to the company’s practice. Our results demonstrate the impact of transportation mode-specific capacities, customer locations, inventory availabilities, and due-date restrictions on outbound logistics costs. Since implementing our load-planning algorithm, WW has achieved cost savings of 4.4 percent over its previous load-planning process.