Questions tagged [simulated-annealing]
The simulated-annealing tag has no usage guidance.
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What is the difference between simulated annealing and deterministic annealing?
Not sure if this is the right place, but I was wondering if someone could briefly explain to me the differences & similarities between simulated annealing and deterministic annealing?
I know that ...
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GenSA simulated annealing solver of R gives EXACTLY the same result regardless of settings
I've been using R's "GenSA" package for simulated annealing to solve a very complicated high dimensional optimization problem (63 unknowns). I found that every time I run GenSA I get exactly the same ...
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101 views
Why are neural networks better at avoiding local minima?
In simulated annealing, from my understanding, it is a process where it stochastically searches the whole landscape at the beginning for the global minima and then hones down on the best solution it ...
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How to simulate spatial point patterns that have spatial structure similar to that of given spatial point pattern?
I have some spatial point pattern X distributed in polygon wind and I wonder how can I simulate different point patterns that by their spatial properties (for example, number of points, spatial ...
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2answers
43 views
Simulated annealing acceptance probability puzzle
My understanding of simulated annealing (SA) is that at any iteration $t$, a new sample $Y_t$ is generated, which, if the objective function $E$ is improved, i.e., $E(Y_t)<E(X_{t-1})$, then $Y_t$ ...
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1answer
73 views
What is the relationship between Metropolis Hastings and Simulated Annealing?
Context and Problem
In the Wikipedia page for Simulated Annealing they state
The simulation can be performed either by a solution of kinetic equations for density functions[2][3] or by using the ...
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1answer
95 views
What is the role of simulated annealing in Gibbs sampling?
While I was reading about Gibbs sampling, I happened to see "simulated annealing" but what is it doing in Gibbs sampling? Although I don't understand the full context of simulated annealing, I am ...
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1answer
63 views
Does the following can be considered a Metropolis Method? [closed]
Suppose, from the current state C it is possible to move to D different neighbouring states. In simulated annealing, we select a neighbouring state $D_i$ randomly and then accept it with probability
$...
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1answer
727 views
Simulated Annealing vs. Basin-hopping algorithm
I was planning to use Simulated Annealing algorithm (scipy.optimize implementation) to optimise my black-box objective function, but the documentation mentions that the method is
Deprecated in ...
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45 views
Multiple Importance Sampling and Metropolis-Hastings on extended state space
Let
$(E,\mathcal E,\lambda),(E',\mathcal E',\lambda')$ be measure spaces
$k\in\mathbb N$
$p,q_1,\ldots,q_k:E\to(0,\infty)$ be probability densities on $(E,\mathcal E,\lambda)$
$w_1,\ldots,w_k:E\to[0,...
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0answers
232 views
Training Neural Network with Simulated Annealing
I am trying to train a simple neural network with simulated annealing. I have programmed a neural network with an input layer of 784 input nodes (28 x 28 pixels, I am using the MNIST database to train)...
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antagonistic simulated annealing
Simulated annealing aims at a series of target distributions
$$\pi_T(x)\propto\exp\{T\,H(x)\}$$
to find the maximum of the function $H$ and its argument
$$\arg_x\max_{x\in \mathfrak X} H(x)$$
if the ...
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0answers
286 views
Simulated Annealing vs SGD with (warm) Restarts
What's the difference between simulated annealing and stochastic gradient descent with restarts? They both seem like they are occasionally going backwards at a decreasing rate. Also what is the ...
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0answers
843 views
Simulated Annealing Parameter Tuning
My question concerns parameter tuning for simulated annealing (SA). I've the following toy equation
$$
y = (x^2+x) \times cos(2x) + 20 \text{ if } x \in (-10, 10)
$$
My problem is that the solution ...
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0answers
282 views
How can I find the bounds that gets Simulated Annealing to converge?
According to Wikipedia on Simulated Annealing,
For any given finite problem, the probability that the simulated annealing algorithm terminates with a global optimal solution approaches 1 as the ...
