Questions tagged [genetic-algorithms]

Questions on genetic algorithms, a family of evolutionary search heuristics. Genetic Algorithms are adaptive heuristic search algorithms based on the evolutionary ideas of natural selection and generics.

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Stochasticity of Genetic Algorithm

I have a set of observations of real data, and a set of Random Variables I produce my self. The goal is to generated Random Variables with the same Distribution as the real data. To investigate the ...
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Difference between selecting a large pool of individuals for reproduction, and selecting two parents specifically

I have implemented a genetic algorithm for an optimization problem and I'm now trying to improve it to see if I can find better solutions or faster convergence. I am confused about the selection part ...
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Are there are satisfying explanations for why genetic algorithms work?

The following commentator writes: Having studied this extensively back when they were called Genetic Algorithms, I would like to offer a few insights. One of the biggest reasons they fell out ...
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Genetic algorithm crossover technique for solving graph colouring problem

I am trying to develop a genetic algorithm to solve a graph colouring problem. The problem is the standard graph colouring problem, given a graph $G = (V,E)$ where $V$ is the set of vertices $V=\{0 \...
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33 views

Genetic programming - tournament selection and elite

I am writing a thesis about automatic GUI testing. In order to find the fittest strategy I am using GP. I am using tournament selection to select chromosomes for the next generation and elitism to ...
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How to improve convergence to an equilibrium value, & damp oscillation?

I am developing a program which seeks strategies for the players A, B in any of a family of simple 2-player gambling-games. The program iterates, using a genetic algorithm to determine, from the ...
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genetic algorithm with different categories of parameters

I am trying to use a genetic algorithm to solve a problem. However, I find it difficult to represent the chromosomes in my problem. In the problem, I have two categories of parameters, and each gene ...
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33 views

Generate a random tree population

Given a unbalanced k-ary tree base (with internal nodes that represent operators and leafs representing values) from the space of all unbalanced k-ary trees ...
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39 views

Choosing Fitness function for float output in Genetic algorithm

I have a NN that has ten outputs. The output values range between 0 and 1. The elements in the target array are all zeros except one element, which is "one". I am searching for a Fitness Function ...
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Chromosome length in Genetic Algorithms

In order to find the appropriate length of chromosomes in GA programming, the author of this book states: Suppose six decimal places for the variables' values is desirable. It is clear that to ...
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52 views

Unknown length of chromosone in genetic algorithm

I've read some about genetic algorithms and the general approach, but I haven't found anything about using it when the length of the solution is unknown. How would the generation of the initial ...
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92 views

adjusted fitness in NEAT algorithm

I'm learning about NEAT from the following paper: http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf I'm having trouble understanding how adjusted fitness penalizes large species and prevents ...
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110 views

Genetic Algorithm for maximization

this may be a shot in the dark, but I am trying to teach myself more machine learning concepts. I have found a textbook and am trying to work through the exercises in it. Could anyone help me with ...
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What use does the predictor stage in a particle filter have?

Im a bit confused about the particle filter. I understand the generic particle filter algorithm but in some literature say particle filter has predictor stage which is not mentioned in the generic ...
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762 views

Improving MSE as fitness function for a genetic algorithm

I am implementing an autoencoder neural network in matlab, the weights of which are being optimised by a genetic algorithm. At the moment I am working on the first layer, trying to get an improved ...
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Design of Evolutionary Algorithm

I was going through some study material and a practice question popped up asking the reader to design an evolutionary algorithm to solve the following task: "A candy bar consists of sugar, choclate, ...
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Genome mutation probability

I am taking an extra course this semester and we were given a series of questions for exam preparation. But I was unable to attend the discussion session and so I have no access to the solutions. I ...
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6 views

Tournament Selection Probability

I am taking an extra course this semester and we were given a series of questions for exam preparation. But I was unable to attend the discussion session and so I have no access to the solutions. I ...
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11 views

Roulette Wheel Selection Probability

I am taking an extra course this semester and we were given a series of questions for exam preparation. But I was unable to attend the discussion session and so I have no access to the solutions. I ...
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17 views

Number of Times to Run an Evolutionary (Genetic) Algorithm

Evolutionary algorithms like genetic algorithms (GAs) are typically run multiple times and the outputted results are averaged across successive runs. However, in the case of long-runtime algorithms (...
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Is this a good way of generating diverse solutions to a problem using a genetic algorithm?

Imagine a complicated blackbox-esque system that has 20 inputs and 5 outputs. I have a set of criteria I am able to use to construct a fitness function. I run a genetic algorithm to deduce values ...
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35 views

What kind of standard deviation must be used in optimization algorithms?

I would like to ask about the standard deviation of objective function value. There are two types of standard deviations: Population standard deviation Sample standard deviation In metaheuristic ...
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52 views

Crossover topologically identical neural networks

I have recently learned about artificial neural networks (very interesting) and genetic algorithms (also very interesting). I have read some suggestions concerning how to crossover two parent neural ...
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1answer
616 views

Using 2-opt Heuristic in a Genetic Algorithm for TSP

I read few papers while trying to find some better approachs to solve the TSP (Traveling salesman problem) as close to the optimal solution as possible. I implemented a Improved Greedy Crossover (...
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151 views

How to find the best parameters of a Genetic Algorithm applied to the TSP problem?

I have an assignement where I need to use a Genetic Algorithm to solve the TSP (Traveling Salesman Problem). I alrerady implemented a solution in C# but the problem is we're asked to use some kind of ...
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Evolutionary Algorithm and Correlation

Note: Not sure with the tags. I'm quite new to this area of Computer Science. I was used to just developing software and applications and applying certain algorithms when necessary. However, I am ...
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123 views

Optimization of coefficients by using genetic algorithm

I want to optimization the coefficient of FIR filter using genetic algorithm method. The main data structures in the Genetic Algorithm are: chromosomes (vector) objective function values fitness ...
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31 views

Appropriate optimization algorithm for constraints having NaN values

I am trying to solve a problem where some of the constraints have NaN values. Which algorithm can be used to handle this kind of problem. In my example I have 3 nonlinear inequality constraints, C(1)&...
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45 views

Handling eqaulity constraints in genetic algorithms

I am trying to solve an optimization problem with strength pareto algorithm (SPEA2). My decision variable have lower and upper bounds as well as an equality constraint (sum(dp) = 1). I am unable to ...
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44 views

Using Genetic Algorithms for volatile problems

Suppose I am looking at an optimization problem with a large number of interconnected constraints, but the solution is - in some regions - extremely volatile (With volatile I mean: small mutations ...
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49 views

Genetic algorithms, Pittsburg - Reach a decision from a set of rules

Consider a binary classification problem. In the Pittsburg approach each member of the population represents a set of rules. Each rule encodes information regarding the data features (that is, the ...
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202 views

Why does my Genetic Algorithm not work for higher number of individuals?

I am using a cooperative coevolutionary genetic algorithm, the algorithm is given in A cooperative coevolutionary approach to function optimization by DeJong et. al. (1994), for optimizing a 62 ...
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Genetic algorithm problem

This is a problem I found in an old exam in my school. I have to solve this Genetic Algorithm problem: N students $x_{1},..,x_{N}$ have answered a quiz of 10 questions (True or False questions) and ...