  This paper presents an adaptive amoeba algorithm to address the shortest path
tree (SPT) problem in dynamic graphs. In dynamic graphs, the edge weight
updates consists of three categories: edge weight increases, edge weight
decreases, the mixture of them. Existing work on this problem solve this issue
through analyzing the nodes influenced by the edge weight updates and recompute
these affected vertices. However, when the network becomes big, the process
will become complex. The proposed method can overcome the disadvantages of the
existing approaches. The most important feature of this algorithm is its
adaptivity. When the edge weight changes, the proposed algorithm can recognize
the affected vertices and reconstruct them spontaneously. To evaluate the
proposed adaptive amoeba algorithm, we compare it with the Label Setting
algorithm and Bellman-Ford algorithm. The comparison results demonstrate the
effectiveness of the proposed method.
