1. Integrating Geographic Information Systems and Vehicle Operations Hal Bowman ESRI, Inc.

2. Why use GIS? Customer Locations Census Tracts Roads Shopping Centers Mountains & Rivers Warehouses Zip Codes Competitor Locations Service/Sales Territories Store Locations Because Everything You Manage is Somewhere :... and somehow connected.

3. GIS creates spatial relationships between otherwise unrelated data “Spatial Join” e.g. Customers e.g. Work Areas Spatial Database Layers

4. GIS allows many types of analysis on Spatial Data GISDataModel Raster Analysis (GRID) Geometric Analysis Network Analysis Cartographic Output ModelingInterfaces Visualization

5. Integration Merging of Two Philosophies GIS Logistics “Better Decisions Through Better Information” - Jack D. - Jack D. “Good Logistics = Sales and Profit” - Gus Pagonis - Gus Pagonis Integrated Solutions

6. Enabling Technologies for Integration with Logistics Spatial Databases –Geocoding capabilities –Routing attributes: Networks GIS tools Logistics tools –Routing capabilities: Solvers

7. Geographic vs. Logical Networks Graph algorithms operate on logical networks. There are a number of issues related to modeling a spatial network as a logical network –One-way or two-way streets and turns –Directionality –Planar or non-planar A geometric junction may really be a bridge over another road

8. Geographic.v.s. Logical Networks

9. A programmer’s library of functions for building applications. Provides embeddable “solvers”, i.e. –Shortest path –Travelling salesman –Service areas – OD or distance matrix calculation

10. ArcLogisticsRoute Complete, Easy to Use Routing Solution for Your Desktop

11. Major functions Geocodes orders: matches address to map Optimize routes & schedules Output: maps, directions, and reports

12. Optimize routes and schedules Minimize f(Time Window Violation Minutes, Cost) While honoring maximum weight, volume, stops, and “specialties”

13. Solution Methodology Build clusters of stops –Near vehicle work areas Sequence stops within routes Swap stops in between routes to improve solution Uses heuristics. We use tabu search.

14. Network Based Clustering A seed point approach takes into account the travel time and distance

15. Swapping Inter-route improvements Inter-route Exchange i+1i+1 j-1 j+1 d i-1 i j-1 j+1 d i-1 i dd jj i+1i+1 j+1j d i-1 i j+1j d i-1 i dd Inter-route Switch Route 1 Route 2

16. Sequencing Intra-route improvements i+1 j+1j d i-1 i j+1j d i-1 i Forward Insertion i+1 j+1j-1 d i j i+1 j+1j d i j Backward Insertion

17. Tabu Search Fred Glover (1989, ORSA Journal of Computing) –Tabu search is an iterative improvement framework that uses a limited memory of past moves to help diversify the search and avoid becoming trapped in local optima. Each time a move is made, it is placed on a list called the tabu-list. When considering a move, it is deemed unchoosable, or tabu, if it is on the tabu-list. Old moves are typically removed from the tabu-list after some number of iterations.

18. ArcView TRACKING ANALYST

19. Key features Real-time display of data Playback of stored data Allows display and analysis as data comes in. Rules to trigger events based on an objects location and/or attribute