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The main methods are based on simulating annealing [14], snake [12, 14] or direct search approaches [15].
It resembles the technique of simulating annealing and is related to several other schemes such as the extended-ensemble method, simulated tempering, and J-walking.
Simulating annealing was used to discover the optimal specification of a series of competition indices, while a neural network was used to discover the best-fit model with a given competition index.
In this paper, I use methods based on simple genetic algorithms with simulating annealing to find good experimental designs for any combination of plots, blocks, treatments, and any set of contrasts.
Consider, for example, the most basic version of optimization by Simulating Annealing (SA) applied to the TSP, which, while theoretically guaranteed to find the optimal solution provided infinite trials [22], does not exploit structure.
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These are simulated annealing, segmented simulated annealing and genetic algorithms.
The 14 minimal hitting sets were also found using a simulated annealing algorithm (Methods, simulated annealing).
a Tracking with simulated annealing.
This leads to simulated annealing type algorithms.
Quantum annealing extends simulated annealing by introducing artificial quantum fluctuations.
The simulated annealing algorithm is described in Table1.
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