A systematic procedure for setting parameters in simulated annealing algorithms
Computers and Operations Research
Computers and Industrial Engineering
Solving Equal Piles with the Grouping Genetic Algorithm
Proceedings of the 6th International Conference on Genetic Algorithms
Adaptive temperature control for simulated annealing: a comparative study
Computers and Operations Research
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Automatic fuzzy decision making system with learning for competing and connected businesses
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
Simulated annealing method has been successfully applied to various combinatorial optimization problems. In the conventional simulated annealing, temperature and local search repetition are determined by simple algorithms with a higher transition probability in the beginning of the search and lower probability toward the end of the search. But these simple methods can cause inefficient search process. In order to overcome this defect, this paper provides an adaptive simulated annealing algorithm using fuzzy logic controller (FLC). FLC can control the temperature and the local search repetition of simulated annealing, thereby making the search process of simulated annealing more efficient. The performance of the proposed method is evaluated and favorably compared with the conventional simulated annealing through traveling salesman problem and equal piles problem.