Self-organization and solution of shortest-path optimization problems with memristive networks.
We show that memristive networks, namely networks of resistors with memory, can efficiently solve shortest-path optimization problems. Indeed, the presence of memory (time nonlocality) promotes self organization of the network into the shortest possible path(s). We introduce a network entropy function to characterize the self-organized evolution, show the solution of the shortest-path problem and demonstrate the healing property of the solution path. Finally, we provide an algorithm to solve the traveling salesman problem. Similar considerations apply to networks of memcapacitors and meminductors, and networks with memory in various dimensions.
Department of Physics and Astronomy, University of South Carolina, Columbia, South Carolina 29208, USA. pershin@physics.sc.edu
Yuriy V
YV
Pershin
Massimiliano
M
Di Ventra