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Solving RealLife Railroad Blocking Problems

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Car. Routing. Railroad Planning Process. 6. 6. 6. Railroad Blocking Problem ... Railroad yards act as hubs where cars change trains. 9. 9. 9. The Railroad ... – PowerPoint PPT presentation

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Title: Solving RealLife Railroad Blocking Problems


1
ESI 6912 Section 6129 (Spring 08)Advanced
Network Optimization
  • Solving Real-Life Railroad Blocking Problems

Ravindra K. Ahuja Professor, Industrial Systems
Engg. University of Florida, Gainesville, FL
ahuja_at_ufl.edu (352) 870-8401 www.ise.ufl.edu/ahuja
2
Reference
  • This presentation is based on the following
    paper
  • R.K. Ahuja, K.C. Jha, and J. Liu
  • Solving Real-Life Railroad blocking Problems
  • To appear in Interfaces, 2007.
  • This paper won INFORMS 2006 Daniel Wagner Prize
    for Excellence in Operations Research.

3
Presentation Outline
  • The Railroad Blocking Problem
  • The VLSN Search Algorithm
  • Case Studies

4
Railroad Planning Process
Railroad Blocking
Service Design
Train Scheduling
Car Routing
Locomotive Scheduling
Crew Scheduling
5
Railroad Blocking Problem
  • Railroad blocking problem is essentially a
    consolidation problem, which is similar to that
    encountered in postal service design.

Gainesville
  • A railroad block is like a mailbag in the postal
    service context.

6
Additional Application Areas
  • Airline Service Design
  • Trucking Service Design
  • Package Delivery Network Service Design
  • Ship Network Service Design

7
Role of Yards in Railroads
  • Railroad yards act as hubs where cars change
    trains.

8
The Railroad Blocking Problem
Destinations
Origins
3,000 nodes
300 nodes
3,000 nodes
9
The Railroad Blocking Model
Railroad Blocking Model
Network
Blocks
Shipment Block Assignments
Shipments
  • Constraints
  • Maximum number of blocks that can be build at a
    node is limited.
  • Maximum volume of shipments passing through a
    node is limited.
  • Objective Function
  • Distances traveled by shipments
  • Intermediate handlings of shipments

10
Integer Programming Formulation
Minimize ?k?K ?(i,j)?A mij ?i?N
?k?K ?(i,j)?O(i) hiyij Subject
to ?(i,j)?O(i) - ?(j,i)?I(i)

for all k ? K ?k?K
uijyij
for all (i, j) ? A
?(i,j)?O(i) yij bi
for all i ? N ?k?K
?(i,j)?I(i) di
for all i ? N yij 0 or
1 and 0 or vk
11
Blocking Problem for a US Railroad
  • Multi-commodity flow network design and routing
    problem
  • 3,000 nodes
  • 50,000 commodities
  • Over a million 0-1 network design variables
  • Hundreds of billions of integer flow variables
  • Substantial amount of costs involved
  • Cost of flow 1,000 - 2,000 million
  • Cost of handling 500 - 1,000 million
  • Currently solved manually.

12
Literature Survey
  • ABM (Algorithmic Blocking Model) by Carl Van Dyke
    1986, 1988
  • Keaton 1989, 1992
  • Newton, Barnhart and Vance 1998
  • Barnhart and Vance 2000
  • The railroad blocking problem remained an
    unsolved problem until recently.

13
Presentation Outline
  • The Railroad Blocking Problem
  • The VLSN Search Algorithm
  • Case Studies

14
A VLSN Search Algorithm
  • We have developed a Very Large-Scale Neighborhood
    (VLSN) Search Algorithm to solve the blocking
    problem.
  • Funded by National Science Foundation.
  • Basic idea
  • Use a simple heuristic to determine the initial
    blocking plan.
  • Use a very large-scale neighborhood (VLSN) search
    algorithm to improve the blocking plan.
  • Keep improving the plan until it stops improving.

15
Neighborhood Search Algorithms
  • Start with a feasible solution x
  • Define a neighborhood of x
  • Identify an improved neighbor y
  • Replace x by y and repeat

VLSN Search Algorithm Size of the neighborhood
is very-very large.
..
16
Two Types of Decisions
  • Design variables
  • Which blocks to build
  • Flow Variables
  • How to route flows on blocks that have been built
  • A Major Assumption
  • All flow is routed on the shortest paths
  • Any problems with this assumption?
  • With this assumption, shortest paths play a very
    important role in solving the blocking problem.

17
Overview of the VLSN Search Algorithm
8
1
5
9
2
7
10
3
6
11
4
  • We reoptimize blocks at one node at a time
    assuming that blocks do not change at other
    nodes.
  • We reoptimize all nodes one-by-one and keep
    performing passes over the nodes until the
    solution terminates to a local optimal solution.

18
Finding Improved Neighbors
  • First Step
  • Select a node and delete all arcs incident on it
  • Reroute the traffic.

19
Finding Improved Neighbors (contd.)
  • Second Step
  • Build arcs one by one with the largest savings.
  • How to compute the potential savings for an arc?
  • Reroute all the shipments to compute the savings
    of an arc.

To compute the savings of an arc, we assess the
savings in the total cost when a block is added.
We do it by solving an all-pairs shortest path
problem after a blocking arc is added.
20
Finding Improved Neighbors (contd.)
  • Third Step
  • Reoptimize all nodes one by one.
  • Fourth Step
  • Perform passes over the nodes until the solution
    is locally optimal.

21
Convergence of the Algorithm
car miles vs. the number of passes
1050
1030
1010
990
970
Car Miles
950
930
910
890
870
0
1
2
3
4
5
6
7
8
9
10
Pass No
Very fast convergence for car miles.
22
Convergence of the Algorithm (contd.)
car handlings vs. the number of passes
1.1
1.05
1
0.95
Car Handlings
0.9
0.85
0.8
0
1
2
3
4
5
6
7
8
9
10
Pass No
Very fast convergence for car handlings.
23
Sensitivity to the Starting Solution
Average Handlings per Car
1
0.95
0.9
0.85
0.8
Handles/Car
0.75
0.7
0.65
0.6
0.55
0.5
0
1
2
3
4
5
6
7
8
9
10
11
Pass No.
Final solution is rather insensitive to the
starting solution.
24
Critical Issue Speed
  • In the course of solving the blocking problem, we
    solve numerous shortest path problems. Thus, it
    is very important that shortest path problems are
    solved very efficiently.
  • Size of the shortest path problem
  • 3,000 x 3,000 9 million shortest path values.
  • It is very time-consuming to update these many
    shortest path values.
  • We take advantage of the hub-spoke configuration
    of the blocking network.

25
Additional Features
  • Block restrictions
  • Some blocks must not be made.
  • Block fixing
  • Some blocks must be made.
  • Block preferences
  • Give preference to some blocks.
  • Shipment-block path fixing
  • Some shipment block sequences must be fixed.

26
Solving Shortest Paths Efficiently
  • Homework Exercise How to solve the shortest path
    problem efficiently for the hub and spoke
    configurations?

Yards
Origins
Destinations
27
Updating Shortest Paths Efficiently
  • How to update all pairs shortest path values when
    an arc is deleted?
  • How to update all pairs shortest path values when
    an arc is added?

28
Incremental Blocking
  • Given an existing blocking plan, change it by a
    specified amount and determine a revised blocking
    plan. Example
  • Make 10 new blocks
  • Delete 10 or more existing blocks
  • Motivation
  • Railroads are not willing to change their
    blocking plans completely.
  • They want to change their plans incrementally,
    little by little and get benefits from
    incremental changes.
  • This strategy is more implementable and involves
    less risk.

29
Train-Friendly Blocking
  • Given a train schedule, make only those blocks
    that require no more than K block swaps.
  • We can set K 0, 1, or 2

New York
Atlanta
Boston
30
Preferential Blocking
  • Railroads may already be making some blocks and
    want to give preference to the bocks they are
    currently making.
  • How to give preferences to some blocks?

31
Presentation Outline
  • The Railroad Blocking Problem
  • The VLSN Search Algorithm
  • Case Studies

32
Computational Results
  • We have performed several case studies on the
    data provided by several US Class I railroads.
  • We performed three types of types
  • Clean-slate blocking
  • Incremental blocking
  • Incremental train-friendly blocking

33
Clean-Slate Blocking Results
  • Conclusion Significant reduction in intermediate
    handlings through better blocking plans.
  • Savings gt 10 million annually

34
Incremental Blocking Results
  • Conclusion Even small changes in the blocking
    plan can have significant impact on intermediate
    handlings.

35
Incremental Train-Friendly Blocking Results
  • Conclusion Train-friendly blocking is almost as
    good as the unrestricted blocking.

36
Homework 2
  • How to solve shortest path problem efficiently in
    the presence of hub and spoke configuration?
  • How to update all pairs shortest path values when
    an arc is deleted?
  • How to update all pairs shortest path values when
    an arc is added?
  • How to do incremental blocking?
  • How to do train-friendly blocking?
  • How to do preferential blocking?
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