Traveling Salesman Problem: Given n cities with known distances between each pair, find the shortest tour that passes through all the cities exactly once before returning to the starting city.

**Examples of search problems**

**Traveling Salesman Problem: **Given** ***n*** **cities with known distances between
each** **pair, find the shortest tour
that passes through all the cities exactly once before returning to the
starting city.

A lower
bound on the length l of any tour can be computed as follows

For each
city i, 1 â‰¤ i â‰¤ n, find the sum s_{i} of the distances from city i to
the two nearest cities.

Compute
the sum s of these n numbers.

Divide
the result by 2 and round up the result to the nearest integer

lb = s /
2

The lower
bound for the graph shown in the Fig 5.1 can be computed as follows:

For any
subset of tours that must include particular edges of a given graph, the lower
bound can be modified accordingly. E.g.: For all the Hamiltonian circuits of
the graph that must include edge (a, d), the lower bound can be computed as
follows:

lb = [(1
+ 5) + (3 + 6) + (1 + 2) + (3 + 5) + (2 + 3)] / 2 = 16.

Applying
the branch-and-bound algorithm, with the bounding function lb = s / 2, to find
the shortest Hamiltonian circuit for the given graph, we obtain the state-space
tree as shown below:

To reduce
the amount of potential work, we take advantage of the following two
observations:

We can
consider only tours that start with a.

Since the
graph is undirected, we can generate only tours in which b is visited before c.

In
addition, after visiting n â€“ 1 cities, a tour has no choice but to visit the
remaining unvisited city and return to the starting one is shown in the Fig 5.2

Root node
includes only the starting vertex a with a lower bound of lb = [(1 + 3) + (3 +
6) + (1 + 2) + (3 + 4) + (2 + 3)] / 2 = 14.

Node 1
represents the inclusion of edge (a, b)

lb = [(1
+ 3) + (3 + 6) + (1 + 2) + (3 + 4) + (2 + 3)] / 2 = 14.

Node 2
represents the inclusion of edge (a, c). Since b is not visited before c, this
node is terminated.

Node 3
represents the inclusion of edge (a, d)

lb = [(1
+ 5) + (3 + 6) + (1 + 2) + (3 + 5) + (2 + 3)] / 2 = 16.

Node 1
represents the inclusion of edge (a, e)

lb = [(1
+ 8) + (3 + 6) + (1 + 2) + (3 + 4) + (2 + 8)] / 2 = 19.

Among all
the four live nodes of the root, node 1 has a better lower bound. Hence we
branch from node 1.

Node 5
represents the inclusion of edge (b, c)

lb = [(1
+ 3) + (3 + 6) + (1 + 6) + (3 + 4) + (2 + 3)] / 2 = 16.

Node 6
represents the inclusion of edge (b, d)

lb = [(1
+ 3) + (3 + 7) + (1 + 2) + (3 + 7) + (2 + 3)] / 2 = 16.

Node 7
represents the inclusion of edge (b, e)

lb = [(1
+ 3) + (3 + 9) + (1 + 2) + (3 + 4) + (2 + 9)] / 2 = 19.

Since
nodes 5 and 6 both have the same lower bound, we branch out from each of them.

Node 8
represents the inclusion of the edges (c, d), (d, e) and (e, a). Hence, the
length of the tour,

l = 3 + 6
+ 4 + 3 + 8 = 24.

Node 9
represents the inclusion of the edges (c, e), (e, d) and (d, a). Hence, the
length of the tour,

l = 3 + 6
+ 2 + 3 + 5 = 19.

Node 10
represents the inclusion of the edges (d, c), (c, e) and (e, a). Hence, the
length of the tour,

l = 3 + 7
+ 4 + 2 + 8 = 24.

Node 11
represents the inclusion of the edges (d, e), (e, c) and (c, a). Hence, the
length of the tour,

l = 3 + 7
+ 3 + 2 + 1 = 16.

Node 11
represents an optimal tour since its tour length is better than or equal to the
other live nodes, 8, 9, 10, 3 and 4.

The
optimal tour is a â†’ b â†’ d â†’ e â†’ c â†’ a with a tour length of 16.

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Artificial Intelligence : Examples of search problems |

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