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Approximating Graphic TSP by Matchings. Tobias Mömke and Ola Svensson KTH Royal Institute of Technology Sweden. Travelling Salesman Problem. Given n cities distance d(u,v ) between c ities u and v Find shortest tour that visits each city once. 1. 1. 2. 2. 1. 1. 2.

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approximating graphic tsp by matchings

Approximating Graphic TSP by Matchings

Tobias Mömke and Ola Svensson

KTH Royal Institute of Technology

Sweden

travelling salesman problem
Travelling Salesman Problem
  • Given
    • ncities
    • distanced(u,v) between citiesu and v
  • Find shortest tour that visits each city once

1

1

2

2

1

1

2

Value = 1+2+1+1 = 5

4

3

1

classic problem
Classic Problem

1800’s

1930’s

70’s

90’s

50’s

60’s

80’s

00’s

2392 cities

13509 cities

  • An optimal tour of 120 cities of (West) Germany
  • Christofidespublishes the famous 1.5-approximation algorithm
  • Held-Karp proposes a very successful heuristic for calculating
  • a lower bound on a tour
  • The lower bound coincides with the value of a linear program known as
  • Held-Karp or Subtour Elimination relaxation

S. Arora and J. S. B. Mitchell publish a

PTAS for Euclidian TSP

C. H. Papadimitriou and S. Vempala:

NP-hard to approximate within 220/219

Applegate, Bixby, Chvatal, Cook, and

Helsgaun find the shortest tour of

24978 cities in Sweden

General form of TSP gets popular and is promoted by

Proctor and Gamble ran a contest

for solving a TSP instance on 33 cities

  • Major open problem to understand the approximability of metric TSP:
  • NP-hard to approximate better than 220/219
  • Christofides’ 1.5-approximation algorithm still best
  • Held-Karp relaxation is conjectured to have integrality gap of 4/3

William Rowan Hamilton and Thomas PenyngtonKirkman

studied related mathematical problems

G. Dantzig, R. Fulkerson, and S. Johnson publish a method for solving the TSP and solve a

49-city instance to optimality

Karl Menger

Hassler Whitney

Merrill Flood

Hamilton

Kirkman

http://www.tsp.gatech.edu/

graphic tsp graph tsp
Graphic TSP (graph-TSP)
  • Given an unweighted graph G(V,E),
  • find spanning Eulerianmultigraph with minimum #edges
  • find the shortest tour with respect to distances

Length = 4n/3 -1

#edges = 4n/3 -1

1

1

4

important special case
Important Special Case
  • Natural problem to find smallest Euleriansubgraph
    • Studied for more than 3 decades
  • Easier to study than general metrics but hopefully shed light on them
    • Still APX-hard
    • Worst instances for Held-Karp lower bound are graphic
    • Any difficult instance to Held-Karp lower bound is determined by a weighted graph with at most 2n-3 edges
    • Until recently, Christofides best approximation algorithm
recent advancements on graph tsp
Recent Advancements on graph-TSP

2000

2005

2010

  • OveisGharan, Saberi & Singh give a
  • (1.5-ε)-approximation algorithm for graph-TSP
  • - First improvement over Christofides
  • Similar to Christofides, but instead of starting with a minimum MST they sample one from the solution of Held-Karp relaxation
  • Analysis requires several novel ideas, like structure of almost minimum cuts

Boyd, Sitters, van der Star & Stougie give a

4/3-approximation algorithm for cubic graphs

7/5-approximation algorithm for subcubic graphs

Conjecture:

subcubic 2-edge connected graphs has a tour of length 4n/3 -2/3

Gamarnik, Lewenstein & Sviridenko give a

1.487-approximation algorithm for cubic 3-edge connected graphs

  • Major open problem to understand the approximability of metric TSP:
  • NP-hard to approximate better than 220/219
  • Christofides’ 1.5-approximation algorithm still best
  • Held-Karp relaxation is conjectured to have integrality gap of 4/3
our results
Our Results

A 1.461-approximation algorithm for graph-TSP

Based on techniques used by Frederickson & Ja’Ja’82 and Monma, Munson & Pulleyblank’90

+ novel use of matchings: instead of only adding edges to make a graph Eulerian we allow for removal of certain edges

Subcubic2-edge-connected graph has a tour of length at most 4n/3 – 2/3

A 4/3-approximation algorithm for subcubic/claw-free graphs

(matching the integrality gap)

outline
Outline
  • Held-Karp Relaxation
  • Given a 2-vertex connected graph G(V,E) find a spanning Eulerian graph with at most 4/3|E| edges
  • Introduce removable edges and prove
  • Comments on general graphs

Subcubic2-edge-connected graph has a tour of length at most 4n/3 – 2/3

held karp relaxation
Held-Karp Relaxation
  • A variable x{u,v} for each pair u,v of cities
  • Very well studied:
  • Any extremepoint has support consisting of at most 2n-3 edges
  • Restriction to 2-vertex-connected graphs is w.l.o.g.
eulerian subgraph of 2 vc graph
Euleriansubgraph of 2-VC graph

Frederickson & Ja’Ja’82 and Monma, Munson & Pulleyplank’90

Use gadgets to make graph cubic

Sample perfect matching M so that each edge is taken with probability 1/3

(Simple application of Edmond’s perfect matching polytope)

Return graph with edge set

An edge is in M with probability 1/3

Expected size of M U E is 4/3|E|

A 2-VC graph has a tour of size 4/3|E|

using matchings to remove edges first idea
Using Matchings to Remove EdgesFirst Idea

Expected size of returned Eulerian graph:

Observation: removing an edge from the matching will still result in even degree vertices

If it stays connected we will again have an Eulerian graph

Same algorithm as before but return

using matchings to remove edges second idea
Using Matchings to Remove EdgesSecond Idea
  • Use structure of perfect matchings to increase the set R of removable edges
  • If it stays connected we will again have an Eulerian graph
  • Define a “removable pairing”
    • Pair of edges: only one edge in each pair can be removed by a matching
  • Graph obtained by removing removable edges such that at most one edge in each pair is removed is connected

R contains all back-edges and

tree-edges paired with a back-edge

If G has degree at most 3 then

size of R is 2b-1

using matchings to remove edges second idea1
Using Matchings to Remove EdgesSecond Idea

Same algorithm as before but return

We have that |R| = 2b -1 and |E| = n-1 + b and thus

result for graphs of max degree 3
Result for Graphs of Max Degree 3
  • Matchings can be used to also remove edges
  • Used structure to increase number of removable edges

“removable pairing”

Subcubic2-edge-connected graph has a tour of length at most 4n/3 – 2/3

A 4/3-approximation algorithm for subcubic/claw-free graphs

(matching the integrality gap)

general case
General Case
  • In degree 3 instances each back-edge is paired with a tree edge
  • In general instance this might not be possible
  • LP prevents this situation:
  • Min Cost circulation flow where the cost makes you pay for this situation
  • Analyze by using LP extreme point structure
final result
Final Result

Christofides

Our

1.0 1.02 1.04 1.06 1.08 1.1

A 1.461-approximation algorithm for graph-TSP

summary
Summary
  • Novel use of matchings
    • allow us to remove edges leading to decreased cost
  • Bridgeless subcubic graphs have tour of size 4n/3 - 2/3
    • Tight analysis of Held-Karp for these graphs
  • 1.461-approximation algorithm for graph-TSP
open problems
Open Problems
  • Find better removable pairing and analysis
    • If LP=n is there always a 2-vertex connected subgraph of degree 3?
  • Removable paring straight forward to generalize to any metric
    • However, finding one remains open
  • One idea is to sample extremepoint, for example:
    • Sample two spanning trees with marginalsxesuch that all edges are removable => 4/3–approximation algorithm