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- W137471503 abstract "Simulated annealing is an optimization technique (Kirkpatrick et al., 1983) that exploits an analogy between combinatorial optimization problems and the statistical mechanics of physical systems. The analogy gives rise to an algorithm for finding near-optimal solutions to any given problem by simulating the cooling of the corresponding physical system. Just as nature, under most conditions, can cool a macroscopic system to, or very close to, its ground state in a short period of time (even though its degrees of freedom are of the order of Avogadro’s number), so simulated annealing rapidly finds a good approximation of the posed problem’s solution. Even though the original class of problems under consideration (Kirkpatrick et al., 1983) was combinatorial optimization, excellent results have also been obtained by applying simulated annealing to seismic inversion (Jakobsen et al., 1987), pattern recognition (Hansen, 1990), and neural networks (Hansen and Salamon, 1989), to name just a few. Simulated annealing is an efficient general-purpose method for handling extremely complicated problems, and as such holds great promise for the areas of climatology and ecology." @default.
- W137471503 created "2016-06-24" @default.
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- W137471503 date "1990-01-01" @default.
- W137471503 modified "2023-10-04" @default.
- W137471503 title "The Use of Simulated Annealing to Solve Extremely Large and Complex Problems" @default.
- W137471503 cites W2024060531 @default.
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- W137471503 doi "https://doi.org/10.1007/978-1-4899-2483-4_6" @default.
- W137471503 hasPublicationYear "1990" @default.
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