Journal Article10.2307/2348448
Optimization Using Simulated Annealing
343
TL;DR: This paper provides an introduction to the practical aspects of function optimization using this approach to simulated annealing, and uses two examples to illustrate the behaviour of the algorithm in low dimensions.
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Abstract: Much work has been published on the theoretical aspects of simulated annealing. This paper provides a brief overview of this theory and provides an introduction to the practical aspects of function optimization using this approach. Different implementations of the general simulated annealing algorithm are discussed, and two examples are used to illustrate the behaviour of the algorithm in low dimensions. A third example illustrates a hybrid approach, combining simulated annealing with traditional techniques.
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References
Optimization by Simulated Annealing
TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
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