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Simulated annealing beats Metropolis in combinatorial optimization. (English) Zbl 1084.68123

Caires, Luís (ed.) et al., Automata, languages and programming. 32nd international colloquium, ICALP 2005, Lisbon, Portugal, July 11–15, 2005. Proceedings. Berlin: Springer (ISBN 3-540-27580-0/pbk). Lecture Notes in Computer Science 3580, 589-601 (2005).
Summary: The Metropolis algorithm is simulated annealing with a fixed temperature. Surprisingly enough, many problems cannot be solved more efficiently by simulated annealing than by the Metropolis algorithm with the best temperature. The problem of finding a natural example (artificial examples are known) where simulated annealing outperforms the Metropolis algorithm for all temperatures has been discussed by Jerrum and Sinclair (1996) as “an outstanding open problem.” This problem is solved here. The examples are instances of the well-known minimum spanning tree problem. Moreover, it is investigated which instances of the minimum spanning tree problem can be solved efficiently by simulated annealing. This is motivated by the aim to develop further methods to analyze the simulated annealing process.
For the entire collection see [Zbl 1078.68001].

MSC:

68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
90C27 Combinatorial optimization
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