Questions tagged [simulated-annealing]
19 questions
8
votes
1 answer
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 scipy 0.14.0, use basinhopping instead
and proposes to…
Tomasz Bartkowiak
- 1,249
- 12
- 20
5
votes
2 answers
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 stochastic sampling method.[1][4] The method is an…
Euler_Salter
- 1,426
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4
votes
0 answers
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 bounces around often between a local maximum and…
Jon
- 2,180
- 1
- 11
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3
votes
1 answer
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 can find. With neural networks, how does it do…
snackbob
- 45
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3
votes
0 answers
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 temperature $T$ increases slowly enough. When…
Xi'an
- 90,397
- 9
- 157
- 575
2
votes
1 answer
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 both methods are used for optimization and both…
Tinu
- 579
- 1
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- 10
2
votes
1 answer
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 autocorrelation of intensity function and etc.) would…
Liudas Daumantas
- 91
- 6
2
votes
0 answers
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), 1 hidden layer with 100 nodes and an output…
user248463
- 31
- 3
2
votes
0 answers
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 difference between SGD with restarts and with warm…
Austin
- 683
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1
vote
1 answer
Simulated Annealing of estimators given PDF
I have the PDF of a Gumbel Distribution which goes like:
$$ f(x) = \frac{e^{-e^{\frac{x-a}{b}} + \frac{x-a}{b}}}{b}; b > 0 $$
The parameters of this distribution are a and b.
I wish to estimate these parameters using simulated annealing (to find the…
WiseRohin
- 13
- 3
1
vote
2 answers
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)
user138668
- 121
- 5
1
vote
1 answer
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 curious about why it is in Gibbs sampling.
StoryMay
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1
vote
1 answer
Does the following can be considered a Metropolis Method?
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
$(D_i) = exp(\frac{−Δ_i}{})$ if $Δ_i\ge0$ and…
Santo
- 41
- 2
1
vote
0 answers
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 annealing schedule is extended.
I looked up the…
eternalmothra
- 145
- 5
0
votes
0 answers
Constant Mode Equation for a Weibull Distribution
I am trying to build a movement class for a simulated annealing algorithm for predicting an optimal spare parts policy. For better or worse I am looking to the Weibull distribution to move about the high dimensional space using a distribution that…
Adam A
- 1