Data Structures and Algorithms
with Object-Oriented Design Patterns in Java 
Dijkstra's algorithm
is a greedy algorithm for solving
the single-source, shortest-path problem on an edge-weighted graph
in which all the weights are non-negative.
It finds the shortest paths from some initial vertex, say 
,
to all the other vertices one-by-one.
The essential feature of Dijkstra's algorithm
is the order in which the paths are determined:
The paths are discovered in the order of their weighted lengths,
starting with the shortest, proceeding to the longest.
For each vertex v,
Dijkstra's algorithm keeps track of three pieces of information,
, 
, and 
:
indicates that the shortest path
to vertex v is known.
Initially, 
for all 
.
is
the length of the shortest known path from to v.
When the algorithm begins, no shortest paths are known.
The distance is a tentative distance.
During the course of the algorithm candidate paths are examined
and the tentative distances are modified.
Initially, 
for all such that 
,
while 
.
to v.
That is, the shortest path from to v has the form
.
Initially, is unknown for all .
Dijkstra's algorithm proceeds in phases. The following steps are performed in each pass:
,
select the vertex v having the smallest tentative distance .
.
,
test whether the tentative distance 
is greater than 
.
If it is, set 
and
set 
.
set to true.
The algorithm terminates after 
passes are completed
at which time all the shortest paths are known.
Table 
illustrates the operation of Dijkstra's
algorithm as it finds the shortest paths starting from vertex b
in graph 
shown in Figure .
| passes | |||||||||||||||||||||||||||||||||||
|
vertex | initially | 1 | 2 | 3 | 4 | 5 | 6 | ||||||||||||||||||||||||||||
| a |  | 3 | b |  | 3 | b | | 3 | b | | 3 | b | | 3 | b | | 3 | b | |||||||||||||||||
| b | 0 | -- | | 0 | -- | | 0 | -- | | 0 | -- | | 0 | -- | | 0 | -- | | 0 | -- | |||||||||||||||
| c | | 5 | b | 4 | a | | 4 | a | | 4 | a | | 4 | a | | 4 | a | ||||||||||||||||||
| d | | | | 6 | c | | 6 | c | | 6 | c | | 6 | c | |||||||||||||||||||||
| e | | | | 8 | c | 8 | c | | 8 | c | | 8 | c | ||||||||||||||||||||||
| f | | | | | 11 | d | 9 | e | | 9 | e | ||||||||||||||||||||||||
Initially all the tentative distances are ,
except for vertex b which has tentative distance zero.
Therefore, vertex b is selected in the first pass.
The mark beside an entry in Table
indicates that the shortest path is known ( 
).
Next we follow the edges emanating from vertex b,
and 
,
and update the distances accordingly.
The new tentative distances for a becomes 3
and the new tentative distance for c is 5.
In both cases, the next-to-last vertex on the shortest path is vertex b.
In the second pass, vertex a is selected and
its entry is marked with indicating the shortest path is known.
There is one edge emanating from a, 
.
The distance to c via a is 4.
Since this is less than the tentative distance to c,
vertex c is given the new tentative distance 4
and its predecessor on the shortest-path is set to a.
The algorithm continues in this fashion
for a total of 
passes
until all the shortest paths have been found.
The shortest-path information contained in the right-most column
of Table
can be represented in the form of a vertex-weighted graph
as shown in Figure .
Figure: The shortest-path graph for .
This graph contains the same set of vertices as the problem graph .
Each vertex v is labeled with the length
of the shortest path from b to v.
Each vertex (except b) has a single emanating edge
that connects the vertex to the next-to-last vertex on the shortest-path.
By following the edges in this graph from any vertex v to vertex b,
we can construct the shortest path from b to v in reverse.
Copyright © 1998 by Bruno R. Preiss, P.Eng. All rights reserved.