Improved Load Plan Design through IP Based Local Search
TITLE: Improved Load Plan Design Through Integer Programming Based Local Search
SPEAKER: Mike Hewitt
Less-than-truckload carriers face an environment with increased competition and customers who demand faster and more reliable service. To respond to these challenges, carriers today seek competitive advantage by reducing costs through improved service network planning. One new direction is to use predictable daily freight volume variations in the planning process to build plans that vary by weekday. Another important new approach is to integrate planning of loaded and empty moves, which have traditionally been conducted sequentially, to plan better utilization of backhaul lanes. Both extensions result in very difficult optimization problems.
In our research, we develop a new heuristic solution technique for these hard problems, which generates day-differentiated service network plans while simultaneously deciding on loaded and empty trailer moves. The method integrates exact optimization into heuristic search by solving an integer program at each iteration that replans the service network for freight destined for a limited set of terminals while holding fixed freight destined for other terminals. Since the method relies on repeated solution of IPs, we also develop classes of valid inequalities and various techniques for reducing their solution time. Computationsl results indicate the methodology uncovers service network plan changes that have the potential to yield reductions of 5% in linehaul costs.
Joint work with Dr.'s Alan Erera, George Nemhauser and Martin Savelsbergh.
This is a joint SCL/DOS Seminar.