Project Director: Manuel D. Rossetti, Ph.D. Co-PI’s: Erhan Kutanoglu, Terry Collins

1. The Analysis of Inter-modal Choice Combinations and Pre-Positioning Strategies for Military Supplies and Materiel Project Director: Manuel D. Rossetti, Ph.D. Co-PI’s: Erhan Kutanoglu, Terry Collins Assistants: Nancy Sloan, Yeu-San Tee, Mee-Ching Chow The Logistics Institute Department of Industrial Engineering University of Arkansas TLI-AR00-2

2. Japan Hawaii DistributionDepots DDC (24) 1999 Puget Sound Germersheim HQ Tobyhanna Hill Susquehanna McClellan Columbus Richmond San Joaquin Norfolk Oklahoma City Barstow Cherry Point Anniston San Diego Red River Warner Robins Albany San Antonio Jacksonville Corpus Christi DLA/TLI 1999/2000 Project • Improve DLA/DDC’s distribution system from suppliers to customers through an integrated systems modeling approach. • Determine the transportation and pre-positioning strategies for various sites on the Pacific Rim AIR LAND SEA DLA Transportation System SUPPLIES Pacific Rim Site

3. San Joaquin Japan Regional Depot Prime Distribution Depot Hawaii Regional Depot Pacific Rim Network What transportation mode combinations should be used (direct vs. inter-modal)? • Where should inventory be pre-positioned? • What type and how much inventory at each location? Can ShipCost provide an answer to this problem?

4. Solution Approach I • Transportation (shipping problem): Build a trade-off spreadsheet model based on ShipCost. ShipCost Software ShipRoutes Spreadsheet Cost & time comparisons for various route/mode combinations • Benefits: • Reduction of the information requirements. • More direct modeling approach. • Easier to perform “what if” analysis.

5. ShipRoutes Demonstration

6. Solution Approach II • Develop inventory model on spreadsheets for proof of concept implementations. Hierarchy of DLA’s Distribution Network Problem: To determine order quantity and reorder point for each level at the least cost and at the required service level.

7. Modeling Requirements • Integration of transportation and inventory model. • Stochastic processes (demand & shipment time variability). • Interdependence between echelons. • Intra-dependence on the same echelon.

8. Inventory-Transportation Model ETAC(s,Q) = setup + holding + transport Order Cost Cycle Stock Shipping Cost speed Safety Stock consistency In-transit Stock Tyworth’s Solution Procedure • Given: - Required Order fill rate (P) - Transportation option • Objective: Minimize Expected Total Annual Cost (ETAC) • Decision variables: s, Q • Constraints: s >=0, Q>0, ES<=TS TS = Target Shortage per cycle = (1-P)Q ES = Expected Shortage per cycle Developed by John E. Tyworth Department of Business Logistics The Pennsylvania State University Smeal College of Business Administration

9. Interactions Between Echelons Warehouse demand process depends on retailer’s inventory policy Retailer’s lead-time relies on warehouse service fill rate

10. Deuermeyer and SchwarZ’sTwo-echelon Inventory Model  Estimate warehouse lead time demand mw = N lR Lw/QR + (1-QR)/2QR s2w = N lR Lw / Q2R • Warehouse backorder (Bw), fill rate (Fw), and expected delay(Tw) • Effective Retailer Lead-Time L = LR + Tw • Estimate retailer performance BR, FR, TR

11. Summary & Recommendation • Integration of the transportation elements into the inventory system will improve the accuracy of modeling. • The modeling of the multi-echelon inventory system provides a good decision making tool for the supply chain network. • These models with the appropriate input data can and should be applied to the DLA distribution system. • Supply chain simulation will allow DLA to evaluate reengineering alternatives and to assess cost savings in advance of implementation.