Title :
A new deterministic annealing algorithm for maximum clique
Author :
Jagota, Arun ; Pelilo, M. ; Rangarajan, Anand
Author_Institution :
Dept. of Comput. Sci., California Univ., Santa Cruz, CA, USA
Abstract :
We propose a new heuristic for approximating the maximum clique problem based on a recently introduced deterministic annealing algorithm which generalizes Waugh and Westewelt´s cluster-competitive net. The approach is centered around a fundamental result proved by Motzkin and Straus in the mid-1960s, and recently expanded in various ways, which allows us to formulate the maximum clique problem in terms of a linearly constrained quadratic program. Preliminary experiments on random as well as standard benchmark graphs are presented which demonstrate the validity of the approach
Keywords :
deterministic algorithms; heuristic programming; simulated annealing; cluster-competitive net; deterministic annealing; generalizes; linearly constrained quadratic program; maximum clique; maximum clique problem; Annealing; Clustering algorithms; Computer science; Computer simulation; Equations; Game theory; Limit-cycles; Neural networks; Quadratic programming; Radiology;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.859445