ISEN 601 Location Logistics

ISEN 601Location Logistics Dr. Gary M. Gaukler Fall 2011

Heuristics • The myopic algorithm identifies the n median locations. • Customers are assigned to their closest median. • Improvement heuristic:

Myopic Example

Improvement Example

Discrete Location Models • “Warehouse Location Problem” • p potential warehouse locations

Warehouse Location Problem • Cost structure is more general: • Fixed costs • Variable shipping/transportation costs

Warehouse Location Problem • Decision variables:

Warehouse Location Problem • Mixed-integer programming formulation:

Warehouse Location Problem • Heuristic algorithms: • Add heuristic • Drop heuristic • Note that total cost generally decreases as facilities are added, and then increases after a point:

Warehouse Location Problem • Add heuristic: • Greedily add facilities to the solution until there is no facility to add that will reduce total cost • Drop heuristic: • Start with one facility at each candidate site. Remove facilities one by one until removal does not decrease total cost

Warehouse Location Problem • Example Add heuristic:

Warehouse Location Problem • Example Drop heuristic:

Transportation • Trends

Transportation • Some terms • FTL: • LTL:

Transportation • Transportation by type • Cost / ton-mile • Air: • FTL: • LTL:

Types of Transportation Paths • Direct Shipment:

Direct Shipment • Math formulation:

Direct Shipment • When to use?

Improvements to Direct Shipment • Option 1: Crossdocking

Improvements to Direct Shipment • Option 2: DC

Improvements to Direct Shipment • Option 3: Delivery rounds / TSP

Traveling Salesman Problem • Problem statement:

Traveling Salesman Problem • BIP formulation:

Traveling Salesman Problem • Subtours:

ISEN 601 Location Logistics