Overview of Intermodal (Multimodal) Supply Chain Optimization and Logistics Scott J. Mason, Ph.D. Fluor Endowed Chair in Supply Chain Optimization and Logistics Professor of Industrial Engineering

Interested Parties Considering international intermodal logistics networks, the key players are operators of Ports Airports Container terminals Freight forwarders Cargo-handling services Container transportation plays a key role, although “high, wide, and heavy” hauling frequently occurs in the absence of any standardized container Scott J. Mason, mason@clemson.edu

An Early Definition of Intermodal Transport International multimodal transport “The carriage of goods by at least two different modes of transport on the basis of a multimodal transport contract from a place in one country at which the goods are taken in charge by the multimodal transport operator to a place designated for delivery situated in a different country.” Three prerequisites: Use at least two different modes of transport (by ship, rail, automobile, airplane) Based on one transport contract A through bill of lading Transport of goods between two different countries Scott J. Mason, mason@clemson.edu

Supply Chain Optimization in Practice Typically not done with Solver  Gurobi, CPLEX, XPressMP, etc. Strategic level studies Quarters, years Optimization, simulation Tactical level studies Months, quarters Optimization, heuristics Operational level studies Days, weeks Heuristics, simulation Scott J. Mason, mason@clemson.edu

Supply Chain Optimization in Practice Step 1: Strategic Network Optimization Deterministic, long time horizon Potential required data inputs List of candidate sites and locations List of demand sites, demand locations Total demand quantities per location Cost per unit of flow and out of each site Cost of transporting units in and out Other constraints, such as Requiring that every demand point is within 500 miles of a warehouse … Scott J. Mason, mason@clemson.edu

Supply Chain Optimization in Practice Step 1: Strategic Network Optimization (cont) Potential output performance measures Total cost Total flow in and out of each node Breakdown of transportation mode usage by lane Manufacturing capacity utilized by the design Which nodes supply which other nodes Which warehouses should supply which customers Which factories should supply which warehouses … Scott J. Mason, mason@clemson.edu

Supply Chain Optimization in Practice Step 2: Network Simulation In addition to those already mentioned for Step 1, other data input requirements may include Rules or policies which govern how inventory is managed and when it is replaced Sourcing and transportation policies Time-dependent demand data Must know how demand arrives over time Scott J. Mason, mason@clemson.edu

Comparing Steps 1 and 2 Network Optimization Network Simulation Evaluates a large number of alternatives Evaluates a few alternatives Models structure only Models structure and behavior Aggregate network statistics Detailed performance statistics No complexity or variance Complexity and randomness Optimal problem solutions (prescriptive) No optimization (descriptive) Determines candidate supply chain structures Useful for final supply chain decision making Scott J. Mason, mason@clemson.edu

An Example Air Distribution Network Cust_1 5 Airport_1 2 Airport_2 DC_1 3-4 1 Cust_2 1-2 7 1-2 7 3 Origin_1 Cust_3 Minimum Transit Time = 22 days (to customer 2) Maximum Transit Time = 29 days (to customer 1)

Example Maritime Distribution Network Cust_1 5 2 DC_1 Minimum Transit Time = 77 days (to customer 2) Maximum Transit Time = 88 days (to customer 1) 1 Cust_2 3 Origin_1 14 1-3 5-10 14 Cust_3 Port_1 Port_2 30 5 WH_1 5

The Multi-Modal Distribution Network Cust_1 5 2 Airport_1 Airport_2 DC_1 3-4 1 Cust_2 1-2 7 1-2 7 3 Origin_1 14 1-3 5-10 14 Cust_3 Port_1 Port_2 30 5 WH_1 5

Additional Distribution Realities 10-12 Cust_1 5 4 2 Airport_1 Airport_2 DC_1 3-4 1 Cust_2 1-2 7 1-2 7 3 12-16 3 Origin_1 14 1-3 5-10 14 Cust_3 Port_1 Port_2 30 5 WH_1 5

Road and Rail Freight Transport Scott J. Mason, mason@clemson.edu

Example Consolidation Networks Scott J. Mason, mason@clemson.edu

Intermodal Research Opportunities Finding the optimal number of terminals in a network Making location decisions for hub-terminals Identifying optimal consolidation strategy Effective allocation of capacity to jobs and scheduling of jobs in terminals Determining truck and chassis fleet size in drayage operations Scott J. Mason, mason@clemson.edu