Simulated Annealing is one of the most important meta-heuristics or generalpurpose algorithms of combinatorial optimization, due to its convergence towards high quality solutions. However, it is associated with a high computational cost and difficulties related to the parameters settings. Therefore the algorithm’s convergence speed has been the subject of a largenumber of research works. Settings the parametersof the algorithm determines the generation of the new solution. One of the most important features in simulated annealing is the choice of the annealing schedule, and many attempts have been made to derive or suggest good schedulesas an optimization technique. The precise rate of cooling is an essential part of Simulated Annealing as it determines its performance. In this paper, we make a comparative study of the performance of simulated annealing using the most important annealing strategies for selecting the initial value of temperature, the cooling schedule, the number of iterations to be performed, and the stopping criterion. The analytical results among different annealing schedules are studied, analyzed and compared. The results are encouraging for application purposes.
(2010). Stochastic Simulated Annealing Algorithms using Different Annealing Schedules: An Analytical Approach. Journal of the ACS Advances in Computer Science, 4(1), 33-57. doi: 10.21608/asc.2010.158215
MLA
. "Stochastic Simulated Annealing Algorithms using Different Annealing Schedules: An Analytical Approach". Journal of the ACS Advances in Computer Science, 4, 1, 2010, 33-57. doi: 10.21608/asc.2010.158215
HARVARD
(2010). 'Stochastic Simulated Annealing Algorithms using Different Annealing Schedules: An Analytical Approach', Journal of the ACS Advances in Computer Science, 4(1), pp. 33-57. doi: 10.21608/asc.2010.158215
VANCOUVER
Stochastic Simulated Annealing Algorithms using Different Annealing Schedules: An Analytical Approach. Journal of the ACS Advances in Computer Science, 2010; 4(1): 33-57. doi: 10.21608/asc.2010.158215