Title :
Demon algorithms and their application to optimization problems
Author :
Wood, Ian ; Downs, Tom
Author_Institution :
Dept. of Electr. & Comput. Eng., Queensland Univ., Qld., Australia
Abstract :
We introduce four new general optimization algorithms based on the `demon´ algorithm from statistical physics and the simulated annealing (SA) optimization method. These algorithms reduce the computation time per trial without significant effect on the quality of solutions found. Any SA annealing schedule or move generation function can be used. The algorithms are tested on traveling salesman problems including Grotschel´s 442-city problem (1984) with results comparable to SA. Applications to the Boltzmann machine are considered
Keywords :
computational complexity; neural nets; simulated annealing; travelling salesman problems; 442-city TSP; Boltzmann machine; SA; computation time; demon algorithms; move generation function; optimization problems; simulated annealing; statistical physics; traveling salesman problems; Computational modeling; Optimization methods; Physics; Processor scheduling; Recurrent neural networks; Sampling methods; Simulated annealing; Temperature; Testing; Traveling salesman problems;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.686028
