Chapter outline

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#### Chapter outline

Section 24.1 presents the Bellman-Ford algorithm, which solves the single-source shortest-paths problem in the general case in which edges can have negative weight. The Bellman-Ford algorithm is remarkable in its simplicity, and it has the further benefit of detecting whether a negative-weight cycle is reachable from the source. Section 24.2 gives a linear-time algorithm for computing shortest paths from a single source in a directed acyclic graph. Section 24.3 covers Dijkstra's algorithm, which has a lower running time than the Bellman-Ford algorithm but requires the edge weights to be nonnegative. Section 24.4 shows how the Bellman-Ford algorithm can be used to solve a special case of "linear programming." Finally, Section 24.5 proves the properties of shortest paths and relaxation stated above.

We require some conventions for doing arithmetic with infinities. We shall assume that for any real number a ≠ -∞, we have a + ∞ = ∞ + a = ∞. Also, to make our proofs hold in the presence of negative-weight cycles, we shall assume that for any real number a ≠ ∞, we have a + (-∞) = (-∞) + a = -∞.

All algorithms in this chapter assume that the directed graph G is stored in the adjacency-list representation. Additionally, stored with each edge is its weight, so that as we traverse each adjacency list, we can determine the edge weights in O(1) time per edge.

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