RelaxationThe single  source shortest paths are based on a technique known as relaxation, a method that repeatedly decreases an upper bound on the actual shortest path weight of each vertex until the upper bound equivalent the shortest  path weight. For each vertex v ∈ V, we maintain an attribute d [v], which is an upper bound on the weight of the shortest path from source s to v. We call d [v] the shortest path estimate. INITIALIZE  SINGLE  SOURCE (G, s) 1. for each vertex v ∈ V [G] 2. do d [v] ← ∞ 3. π [v] ← NIL 4. d [s] ← 0 After initialization, π [v] = NIL for all v ∈ V, d [v] = 0 for v = s, and d [v] = ∞ for v ∈ V  {s}. The development of relaxing an edge (u, v) consists of testing whether we can improve the shortest path to v found so far by going through u and if so, updating d [v] and π [v]. A relaxation step may decrease the value of the shortest  path estimate d [v] and updated v's predecessor field π [v]. Fig: Relaxing an edge (u, v) with weight w (u, v) = 2. The shortestpath estimate of each vertex appears within the vertex. (a) Because v. d > u. d + w (u, v) prior to relaxation, the value of v. d decreases (b) Here, v. d < u. d + w (u, v) before relaxing the edge, and so the relaxation step leaves v. d unchanged. The subsequent code performs a relaxation step on edge (u, v) RELAX (u, v, w) 1. If d [v] > d [u] + w (u, v) 2. then d [v] ← d [u] + w (u, v) 3. π [v] ← u
Next TopicDijkstra's Algorithm
