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Integrating Geographic Information Systems and Vehicle Operations. Hal Bowman ESRI, Inc. Spatial Database Layers. e.g. Customers. “Spatial Join”. e.g. Work Areas. GIS creates spatial relationships between otherwise unrelated data. Geometric Analysis. Network Analysis. GIS Data

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Presentation Transcript
gis creates spatial relationships between otherwise unrelated data

Spatial Database

Layers

e.g. Customers

“Spatial Join”

e.g. Work Areas

GIS creates spatial relationships between otherwise unrelated data
gis allows many types of analysis on spatial data

Geometric Analysis

Network Analysis

GIS

Data

Model

Cartographic Output

Raster Analysis (GRID)

Modeling

Interfaces

Visualization

GIS allows many types of analysis on Spatial Data
integration
Integration

Merging of Two Philosophies

GIS

Logistics

“Better Decisions

Through Better

Information”

- Jack D.

“Good Logistics =

Sales and Profit”

- Gus Pagonis

Integrated Solutions

enabling technologies for integration with logistics
Enabling Technologiesfor Integration with Logistics
  • Spatial Databases
    • Geocoding capabilities
    • Routing attributes: Networks
  • GIS tools
  • Logistics tools
    • Routing capabilities: Solvers
geographic vs logical networks
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
slide8
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
slide9

ArcLogistics

Route

Complete, Easy to Use Routing Solution for Your Desktop

major functions
Major functions
  • Geocodes orders: matches address to map
  • Optimize routes & schedules
  • Output: maps, directions, and reports
optimize routes and schedules
Optimize routes and schedules
  • Minimize

f(Time Window Violation Minutes, Cost)

  • While honoring maximum weight, volume, stops, and “specialties”
solution methodology
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.
network based clustering
Network Based Clustering

A seed point approach

takes into account the

travel time and distance

swapping

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Inter-route Switch

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Inter-route Exchange

Swapping
  • Inter-route improvements
sequencing

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Forward Insertion

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Backward Insertion

Sequencing
  • Intra-route improvements
key features
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