Spatial Network Analysis for Optimization and Routing Solutions

1. Network Analysis, Routing Dawn Wright and Jim Graham

2. Networks • Systems of connected lines • Weights along edges Junctions Or Nodes Edges or Links

3. Spatial Examples • Electrical Grid • Power lines and transfer stations • Roadways (highways, freeways) • Roads and intersections • Pipelines • Canals, streams, rivers • Shipping lanes • Migration paths • Social networks (non-spatial?)

4. Example: Freeways

5. Network Rules • Edge-Junction: • Which edges can connect to a junction • Examples: • Three-phase 240 volt vs. high voltage • Freeway to overpass • Edge-Edge: • Freeway to Freeway: overpass with clover leaf • Freeway to Highway: overpass with lights • Highway to Highway: lights • Road to Road: stop signs

6. Weights • Edge • Type of surface, speed limit -> Travel time • Junction • Type of intersection -> stop time • Barrier • Stops travel, can be temporal • Examples: • Construction • Raising bridges • Can be directional (i.e. fish move downstream easier than upstream)

7. Sources & Sinks • Sources • Add to the network • Examples: • Downtown at 5:00pm • Spawning areas • Sinks • Terminate a network • Examples: • Suburbs at 5:00pm • The ocean

8. Network Problems • Shortest path: Route • Minimizing total distance traveled • Minimizing the largest distance traveled by any customer • Maximizing profit • Minimizing a combination of travel distance and facility operating cost

9. Network Analyst • Finding Optimal Routes • Route Solver Properties • Service Area Solver Properties • Closest Facility Solver Properties • OD Cost Matrix Solver Properties • Vehicle Routing Problem Solver Properties • Location Allocation Solver Properties

10. Shortest Path - Route • Stops • Time windows for deliveries • Etc.

11. Closest facility analysis • Multiple origins, destinations, facilities along the route

12. Optimization & Routing for Emergency/Disaster Response • Kim et al. 2006 – PARs, Protective Action Recs d= interpolated, shortest-distance of wildfire to community d1 = shortest distance before PAR d2 = shortest distance after PAR t = time PAR was issued t1 = time last known fire perimeter at d1 t2 = time last known fire perimeter at d2

13. Fire Origin to Communities:Estimate Avg. Speed of Fire Between Known Perimeters Kim et al. 2006

14. Additional Slides

15. Origin-Destination (OD)Cost Matrix

16. Routing service technicians for Schindler Elevator. Every day this company’s service crews must visit a different set of locations in Los Angeles. GIS is used to partition the day’s workload among the crews and trucks (color coding) and to optimize the route to minimize time and cost.

17. Gateway to the Literature • Cova, T. and Johnson, J.P., 2002. Microsimulation of neighborhood evacuations in the urban-wildland interface. Environment and Planning A, 34: 2211-2229. • Cova, T. J., P. E. Dennison, et al. 2005. Setting wildfire evacuation trigger points using fire spread modeling and GIS. Transactions GIS, 9(4): 603-617. • Kim, T.H., Cova, T.J., and Brunelle, A., 2006. Exploratory map animation for post-event analysis of wildfire protective action recommendations. Natural Hazards Review, 7(1): 1-11. • Monteiro, C., Ramirez-Rosado, I., Zorzano-Santamaria, P. and Fernandez-Jimenez, L.A., 2005. GIS spatial analysis applied to electric line optimization. IEEE Transactions on Power Delivery, 20(2): 934-942.