Abstract
Simulated annealing is a method suitable for solving optimization problems of a large scale specially ones where a desired global extremum is hidden among many local extrema. The idea of the method is an analogy with thermodynamics, specifically with the way that liquids freeze and crystallize or metals cool and anneal. For slowly cooled systems, nature is able to find the minimum energy state. If a liquid metal is cooled quickly, it does not reach this state, but rather ends up in a polycrystalline or amorphous state having higher energy. So slow cooling is essential for ensuring that a low-energy state is achieved. Simulated annealing randomizes the iterative improvement procedure and also allows occasional uphill moves in attempt to reduce the probability of being stuck at local optimal solution. These uphill moves are controlled probabilistically by the temperature, and become less and less likely toward the end of the process, as the value of temperature decreases.
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Čepin, M. (2011). Simulated Annealing. In: Assessment of Power System Reliability. Springer, London. https://doi.org/10.1007/978-0-85729-688-7_19
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DOI: https://doi.org/10.1007/978-0-85729-688-7_19
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