Solving the Vehicle Routing Problem with Multiple Multi-Capacity Vehicles

1
Solving the Vehicle Routing Problem withMultiple
Multi-Capacity Vehicles

• Michael Sanders

2
Goals

• Create a program that given
• List of delivery points
• Number and capacity of vehicles
• List of roads
• Return a list of routes that most efficiently
  utilize vehicles
• Efficiency undefined, but probably will be
  product delivered over distance traveled

3
Scope

• Heuristics
• Needed for program to identify optimal placement
  of delivery point into a route and assigning a
  vehicle to a route
• Will probably need new heuristic, although some
  already exist for this problem
• A search
• Used to find shortest route between two locations
• Will use heuristic based on geographical
  coordinates

4
Previous Research

• Vehicle Routing Problem (VRP)
• Extensively researched
• Solutions
• Agent architecture
• Used agents to represent vehicles and
  auctioneer that assigned customers to routes
• Ant colony optimization
• Could solve variants of VRP

5
Variants of VRP

• Variants
• VRP with Time Windows (VRPTW)
• Requires deliveries to be in specific time ranges
  for each delivery
• Multi-Depot VRP (MDVRP)
• Multiple origins for vehicles

6
Components

• Route finder
• Given two intersections, find shortest-time route
  between the two
• Delivery route creator
• Using list of delivery points and quantity to be
  delivered, utilizes other component to most
  efficiently deliver the product

7
Route Finder

• Program responsible finding quickest route
• Uses A search with a geographic heuristic
• Will use latitude and longitude coordinates to
  help find best route
• Will use speed limit information as well to find
  quickest route as well
• Uses Fairfax Cty and Census data

8
Delivery Route Creator

• Using previous component, will create routes and
  assign vehicles to them
• Will involve heuristic to determine best delivery
  point to be added to route and when new route
  should be created

9
Timeline

• Route finder should be complete NLT ½ through
  second quarter
• Route creator will follow after that
• Aiming to be done early spring in time for
  volunteer groups delivery day to test program

10
Testing

• Currently running route finder program and giving
  it two intersections and evaluating result
  against known route information
• As heuristic is implemented, results can be
  compared against commercially available mapping
  programs

11
Other Information

• Language
• Ruby
• Problems
• Road data
• Not complete in certain fieldsaddresses,
  coordinates, speed limits, etc.
• Delivery data is not standardized
• Road names not standard throughout list

12
Things Learned

• Use of hash tables and array storage
• Inprocessing of data

13
Testing Analysis

• Route finder is currently successful so far
• Is capable of finding route between two
  intersections near each other
• However, is very inefficient
• Breadth-first search
• Given complexity of local road network, finding a
  route between intersections that are far away can
  take days

14
Main Points

• Importance of the route finder
• Crucial to the route creators ability to
  function
• Ways of implementing a heuristic in the route
  creator
• Some ideas from literature research