Description
1. Apply Kruskal’s algorithm to the graph shown in Figure 1 to obtain its minimum
spanning tree. Show the intermediate steps of applying the algorithm. Draw the final
minimum spanning tree.
a
b
c
d
e
f
9
5
2
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7
5
3
1 6
Figure 1: A weighted undirected graph.
2. Suppose that you are given a directed acyclic graph G = (V, E) with real-valued edge
weights and two distinct nodes s and d. Describe an algorithm for finding a longest
weighted simple path from s to d. For example, for the graph shown in Figure 2, the
longest path from node A to node C should be A → B → F → C. If there is no path
exists between the two nodes, your algorithm just tells so. What is the efficiency of
your algorithm? (Hint: consider topological sorting on the DAG.)
3. You are given a directed graph G = (V, E) on which each edge (u, v) ∈ E has an
associated value r(u, v), which is a real number in the range 0 ≤ r(u, v) ≤ 1 that
represents the reliability of a communication channel from vertex u to vertex v. We
interpret r(u, v) as the probability that the channel from u to v will not fail, and we
assume that these probabilities are independent. Give an efficient algorithm to find
the most reliable path between two given vertices. (Hint: consider the shortest path
algorithm.)
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A
D E F
B C
G
H
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8 3
1
9
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Figure 2: A weighted directed graph.
4. Let G = (V, E) be a connected, undirected graph. Give an O(|V |+|E|)-time algorithm
to compute a path in G that traverses each edge in E exactly once in each direction.
For example, for the graph shown in Figure 3, one path satisfying the requirement is
A → B → C → D → C → A → C → B → A
Note that in the above path, each edge is visited exactly once in each direction. (Hint:
consider the graph search algorithm.)
A
B C
D
Figure 3: An undirected graph.
5. Apply the Bellman-Ford algorithm to the graph shown in Figure 4 to obtain the shortest
path from node a to every other node in the graph. Show the intermediate result.
You should run the full version of the Bellman-Ford algorithm (i.e., including the last
iteration that checks the existence of a negative cycle). If there is a negative cycle,
report so. When running the algorithm, besides keeping track of the shortest path
length, you should also keep track of the predecessor on the shortest path. If there is
no negative cycle, please write the final shortest path and its length for each destination
node.
6. Prove the following early stopping criterion for the Bellman-Ford algorithm. For a given
graph G = (V, E) and a source vertex s, if you apply the Bellman-Ford algorithm and
find that that for a j < |V | − 1, L(v, j) = L(v, j − 1) for all vertices v ∈ V , then you
can stop and claim that there is no negative cycle and the length of the shortest s-v
path is L(v, j) for all v ∈ V . Here L(v, i) is the length of the shortest s-v path with at
most i edges.
2
a
b
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d
e
f
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-3
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Figure 4: A weighted directed graph.
7. Consider the problem of neatly printing a paragraph with a monospaced font (all
characters having the same width) on a printer. The input text is a sequence of n
words of lengths l1, l2, . . . , ln, measured in characters. We want to print this paragraph
neatly on a number of lines that hold a maximum of M characters each. Our criterion
of “neatness” is as follows. If a given line contains words i through j, where i ≤ j, and
we leave exactly one space between words, the number of extra space characters at the
end of the line is M − j + i −
Pj
k=i
lk, which must be nonnegative so that the words
fit on the line. We wish to minimize the sum, over all lines except the last, of the
cubes of the numbers of extra space characters at the ends of lines. Give a dynamicprogramming algorithm to print a paragraph of n words neatly on a printer. What
is the running time of your algorithm?
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