Title :
A consensus-function artificial neural network for map-coloring
Author :
Tambouratzis, T.
Author_Institution :
NCSR, Inst. of Nucl. Technol.-Radiat. Protection, Athens, Greece
fDate :
10/1/1998 12:00:00 AM
Abstract :
A harmony theory artificial neural network solution to the map coloring problem is presented. Map coloring aims at assigning a unique color to each area of a given map so that no two adjacent areas receive identical colors. The harmony theory implementation is able to determine whether the map coloring problem can be solved with a predefined number of colors as well as which is the smallest number of colors that can solve the map coloring problem. The present implementation directly encodes the given problem into the artificial neural network so that a solution is represented simply by node activation. Additionally, the consensus function of harmony theory produces a quick and definite solution to the colorability problem, obviating the need for manual validation of the result
Keywords :
graph colouring; neural nets; optimisation; adjacent areas; colorability problem; consensus function; consensus-function artificial neural network; harmony theory artificial neural network solution; harmony theory implementation; map coloring problem; node activation; unique color; Artificial intelligence; Artificial neural networks; Biological neural networks; Biological processes; Central nervous system; Color; Graph theory; Mathematical model; Neurons; Surges;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.718521