Author_Institution :
Dept. of Mech. & Mechatron. Eng., Univ. of Stellenbosch, Matieland, South Africa
Abstract :
For a given graph (or network) G, consider another graph G´ by adding an edge e to G. We propose a computationally efficient algorithm of finding e such that the second smallest eigenvalue (algebraic connectivity, lambda2(G´)) of G´ is maximized. Theoretically, the proposed algorithm runs in O(4 mnlog(d/isin)), where n is the number of nodes in G, m is the number of disconnected edges in G, d is the difference between lambda3(G) and lambda2(G), and isin > 0 is a sufficiently small constant. However, extensive simulations show that the practical computational complexity of the proposed algorithm, O(5.7 mn), is nearly comparable to that of a simple greedy-type heuristic, O(2 mn). This algorithm can also be easily modified for finding e which affects lambda2(G) the least.
Keywords :
computational complexity; eigenvalues and eigenfunctions; graph theory; greedy algorithms; matrix algebra; optimisation; Laplacian matrix; algebraic connectivity; bisection algorithm; computational complexity; eigenvalue; graph edge; greedy-type heuristics; maximization; Africa; Automatic control; Automation; Computational complexity; Computational modeling; Computer networks; Eigenvalues and eigenfunctions; Laplace equations; Relays; Robust stability; Laplacian matrix; algebraic connectivity;