Reading time: less than 1 minute
What is Simulated Annealing?
Simulated annealing is an optimization method for finding the global optimum of a function. The algorithm is similar to a hill_climbing algorithm.
Comparison with Hill Climbing
Simulated annealing, just like hill climbing, has one current solution. In each iteration, that solution takes a random step and either improves, stays the same, or becomes worse.
If you find this work useful, please cite it as:
title = "Simulated annealing",
author = "Yaltirakli, Gokberk",
journal = "gkbrk.com",
year = "2022",
url = "https://www.gkbrk.com/wiki/simulated-annealing/"
Not using BibTeX? Click here for more citation styles.
Gokberk Yaltirakli, "Simulated annealing", June, 2022. [Online]. Available: https://www.gkbrk.com/wiki/simulated-annealing/. [Accessed Jun. 24, 2022].
Yaltirakli, G. (2022, June 24). Simulated annealing. https://www.gkbrk.com/wiki/simulated-annealing/
Gokberk Yaltirakli, Simulated annealing, GKBRK.COM (Jun. 24, 2022), https://www.gkbrk.com/wiki/simulated-annealing/