Questions tagged [mutation-operators]

For questions about methods (or operators) to mutate individuals (or chromosomes) in the context of evolutionary algorithms.

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What is the use of utilizing q-Gaussian mutation operators in evolutionary algorithms?

There are great numbers of evolutionary algorithms for optimization of engineering problems which each of them gives its own objective function value in a defined problem. Using the q-Gaussian ...
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Should hyper-parameters used in the mutation operator be fixed or variable?

Let's say I have a function $f(p_{i,t})$ and want to optimize $p_{i,t}$ so that I minimize a certain loss. Here, $p_{i,t}$ is the individual $i$ at iteration $t$. Now, $p_{i,t}$ can live anywhere ...
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How to handle equality constraints in the mutation operation of evolutionary algorithms?

I am new in evolutionary algorithms field. I have a chromosome of 6 variables (real variable), where the sum of these variables is equal to 1. I am looking for mutation formulas that can generate a ...
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How should the 1-point crossover and mutation be defined for the problem of finding the largest circle that does not enclose any point?

For a random scattering of points, in a bounded area, the goal is to find the largest circle that can be drawn inside those same bounds that does not enclose any points. Solving this problem with a ...
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What is the impact of changing the crossover and mutation rates?

What is the impact of using a: low crossover rate high crossover rate low mutation rate high mutation rate
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What does "In each generation, 25% of offspring resulted from mutation without crossover" mean in the context of NEAT?

I am reading through the NEAT paper. In parameter settings, page 15, there is: In each generation, 25% of offspring resulted from mutation without crossover. What does it mean?
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Do I have to crossover my node genes in NEAT, and how?

I'm currently trying to code the NEAT algorithm by myself, but I got stuck with two questions. Here they are: What happens if during crossover a node is removed (or disabled) and there's a connection ...
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How can we design the mutation and crossover operations when the order of the genes in the chromosomes matters?

Consider an optimization problem that involves a set of tasks $T = \{1,2,3,4,5\}$, where the goal is to find a certain order of these tasks. I would like to solve this problem with a genetic algorithm,...
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How to find optimal mutation probability and crossover probability?

I have a genetic algorithm that maximizes a fitness function with two variables f(X,Y). I have been running the algorithm with various parameters in mutation and crossover probability (0.1, 0.2, ...) ...
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How to handle infeasibility caused due to crossover and mutation in genetic algorithm for optimization?

I have chromosomes with floating-point representation with values between $0$ and $1$. For example Let $p_1 = [0.1, 0.2, 0.3]$ and $p_2 = [0.5, 0.6, 0.7]$ be two parents. Both comply with the set of ...
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Why do we apply the mutation operation after generating the offspring?

Why do we apply the mutation operation after generating the offspring, in genetic algorithms?
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What is the difference between "mutation" and "crossover"?

In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?
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How do mutation and crossover work with real-valued chromosomes?

How exactly are "mutation" and "cross-over" applied in the context of a genetic algorithm based on real numbers (as opposed to just bits)? I think I understood how those two phases are applied in a "...
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Is there an efficient way to implement a random crossover of individuals stored in a matrix?

I am using a GA to optimise an ANN in Matlab. This ANN is pretty basic (input, hidden, output) but the input size is quite large (10,000) and the output size is 2 since I have to classes of images to ...
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Why is cross-over a part of genetic algorithms?

Genetic Algorithms has come to my attention recently when trying to correct/improve computer opponents for turn-based strategy computer games. I implemented a simple Genetic Algorithm that didn't use ...
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