A systematic procedure for setting parameters in simulated annealing algorithms.
Moon-Won ParkYeong-Dae KimPublished in: Comput. Oper. Res. (1998)
Keyphrases
- simulated annealing
- learning algorithm
- recently developed
- orders of magnitude
- computational cost
- hill climbing
- computational complexity
- artificial neural networks
- significant improvement
- computationally efficient
- optimization methods
- parameter tuning
- machine learning
- search procedure
- parameter values
- hybrid algorithm
- free parameters
- computational efficiency
- tabu search
- benchmark datasets
- constraint satisfaction problems
- optimization problems
- lower bound
- search algorithm
- computer vision