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Questions tagged [simulated-annealing]

For questions related to the simulated annealing algorithm (SA), which is a probabilistic algorithm that attempts to find the global optimum of a function. SA can e.g. be used to solve the travelling salesman problem (TSP).

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When should I use simulated annealing as opposed to a genetic algorithm?

What kind of problems is simulated annealing better suited for compared to genetic algorithms? From my experience, genetic algorithms seem to perform better than simulated annealing for most problems....
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What are examples of daily life applications that use simulated annealing?

In AIMA, 3rd Edition on Page 125, Simulated Annealing is described as: Hill-climbing algorithm that never makes “downhill” moves toward states with lower value (or higher cost) is guaranteed to be ...
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What is the basic purpose of local search methods?

I read about the hill climbing algorithms, the simulating annealing algorithm, but I am confused. What is the basic purpose of local search methods?
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1answer
1k views

How is simulated annealing better than hill climbing methods?

In hill climbing methods, at each step, the current solution is replaced with the best neighbour (that is, the neighbour with highest/smallest value). In simulated annealing, "downhills" moves are ...
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Memory intensive local search methods

I have been studying local search algorithms such as greedy hill climbing, stochastic hill climbing, simulated annealing etc. I have noticed that most of these methods take up very little memory as ...